Gadolinium-based contrast agents enhance visibility but also pose a significant health risk. A new AI-powered virtual MRI imaging technique is designed to offer a safer diagnostic approach.
Medical imaging methods are often affected by background noise, which can obscure fine anatomical details. A new approach to solve this problem draws inspiration from quantum mechanics.
Microsatellite instability-high (MSI-H) tumors are associated with better clinical outcomes. A novel AI model for accurate MSI prediction could help battle gastric and colorectal cancers.
Using electrodes implanted in the brain, researchers observed specific brain waves that could serve as a biomarker for obsessive-compulsive disorder (OCD) and are an important step towards more targeted treatments.
A neural network AI has been trained to detect cardiac amyloidosis from a single echocardiogram video of the heart's apical four-chamber view and differentiate it from similar heart conditions.
A novel deep-learning approach automatically finds and classifies microcalcifications found in mammography images—bringing both accuracy and consistency to breast-cancer screening.
Using AI to analyse ultrasound scans can detect up to 35% more risk pregnancies than scans performed by healthcare professionals without AI decision support, according to new results.
United imaging announces the successful installation of their digital PET/CT system uMI 550 at Centre Mèdic Alomar in Barcelona. Equipped with comprehensive cardiac imaging features, its use extends beyond cardiology.
A network of artificial neurons imitating the human brain could help identify patients at risk of a serious arrhythmia from an ECG and avoid many cases of sudden cardiac death, a new study suggests.
By using AI to analyse ECG data, researchers created an algorithm to predict the biological age of the heart. This could be used to identify those most at risk of cardiovascular events and mortality.
New research reveals that self-generated electrical activity of small cell lung cancer (SCLC) directly promotes tumor metastasis and progression. This may provide new avenues for future treatments.
Researchers developed an advanced AI tool for automatic analysis of colorectal cancer tissue slides. The new model outperformed all predecessors in the classification of tissue microscopy samples.
HighlightsIntelligent NR is Canon's AI image processing option, developed using machine learning and an existing clinical image database to create a neural network for deep-learning. By identifying the characteristics of noise and applying the pre-learned neural network, a noise-reduced image is created. Key Features: High quality diagnostic images with reduced noiseNo noticeable loss of…
New insights on the degradation of implantable chips in the body could lead to enhanced longevity of the chips and better treatments for patients with Parkinson's or clinical depression.
More than just a sports injury: A new study shows that head trauma may activate latent viruses, leading to neurodegenerative conditions such as Alzheimer’s disease and Parkinson’s disease.
Ovarian cancer is common and often only detected by chance. A newly developed AI-based model could help differentiate between benign and malignant ovarian lesions.
Scientists have now discovered that the heart has its own complex nervous system – a 'mini brain', if you will – that is crucial to controlling its rhythm.
Precise segmentation of anatomical structures greatly benefits cancer diagnosis. Using AI and deep learning methods, researchers are developing a high-precision 3D viewer software for medical image data.
In the world of theatre, the ‘deus ex machina’, the god from the machine, is a dramaturgical trick to resolve seemingly unsolvable conflicts. Can artificial intelligence (AI) also be such a universal problem solver for internal medicine? At the Annual Congress of the German Society of Internal Medicine (DGIM), Dr Isabella Wiest explored the potential – and limitations – of AI helpers.
Alzheimer’s disease may damage the brain in two distinct phases, based on new research funded by the National Institutes of Health (NIH) using sophisticated brain mapping tools.
Using smartly trained neural networks, researchers at TU Graz have succeeded in generating precise real-time images of the beating heart from just a few MRI measurement data.
Researchers have developed an artificial intelligence which can differentiate cancer cells from normal cells, as well as detect the very early stages of viral infection inside cells.
The interpretation of prostate MRI is notoriously difficult. Annotating AI shows promise to help improve diagnostic performance through increased cancer detection rates with fewer false positives.
A team of Danish and Dutch researchers has combined an AI diagnostic tool with a mammographic texture model to improve the assessment of short- and long-term breast cancer risk. This new approach represents a significant step forward in refining the ability to predict the complexities of breast cancer risk.
Using ultrasound imaging to detect Covid-19 infections, a new automated detection tool could help doctors in the emergency room diagnose patients quickly and accurately.
Some year in this decade, AI tools will become ubiquitous within clinical laboratories. AI has the potential to increase the accuracy of laboratory testing and improve the quality and efficiency of operations and service of testing labs.
Artificial Intelligence has helped scientists reveal a new form of aggressive prostate cancer which could revolutionise how the disease is diagnosed and treated in the future.
Breast cancer has no “one size fits all” therapy approach: subtypes differ significantly in malignancy, progression, and treatment response. Therefore, the more is known about the type of carcinoma in a patient, the better the outcome. At the annual scientific EUSOBI meeting in Valencia, Dr Ramona Woitek pointed out the potential of novel imaging techniques and computational image analysis…
Researchers in Singapore have developed an AI-based software to assist in the early detection of breast cancer. Using thermal imaging, the program assesses the malignancy of a tumour.
Certain genetic features are crucial for treatment decisions for AML leukaemia. A team from Münster shows how an AI-based method can predict these features from images of bone marrow smears.
A feasibility study by Swiss researchers shows that AI systems are able to reliably predict therapeutic success in patients with borderline personality pathology by detecting emotions on their face.
Research from Shenzhen proposes an integrated diagnosis model for automatic classification of adult-type diffuse gliomas directly from annotation-free standard whole-slide pathological images.
Ten times more detail than current 7T scanners, over 50 times more than 3T: A new type of functional MRI will allow neuroscientists to more precisely localize and trace brain networks.
The brain of soccer fans is wired in a special way. Now, new research looks into how these MRI insights translate into fanaticism - if you prefer the full term - in other areas, such as politics.
Ultrasound technology now plays a vital role in clinical diagnosis and management. Significant advances in point-of-care ultrasound (POCUS) have made it a versatile tool for assessment, diagnosis, and follow-up across various fields. New developments continue to expand its applications, improving patient care and outcomes.
Machine learning and AI are playing an increasingly important role in medicine and healthcare, and not just since ChatGPT. This is especially true in data-intensive specialties such as radiology, pathology or intensive care. The quality of diagnostics and decision-making via AI, however, does not only depend on a sophisticated algorithm but – crucially – on the quality of the training data.
Philips and Quibim have signed a multi-year agreement to work on an integrated solution including an AI-based software to automate real-time prostate gland segmentation in MR images.
Researchers from Finland have developed an artificial intelligence tool for automatic colorectal cancer tissue analysis that outperforms prior methods.
Voice pathology detection (VPD) can detect abnormal vibrations in the vocal cords caused by conditions like cancer and cysts. Now, researchers have found a way to make the method more reliable.
A new artificial intelligence (AI) model combines imaging information with clinical patient data to improve diagnostic performance on chest X-rays, a new study finds.
It had long been recognized that the brain was made up of two types of cells, neurons and glial cells. Now, neuroscientists discovered an additional type - with huge implications for brain disorders.
For the first time, researchers show that AI-based predictions can deliver comparable results to clinical tests on biopsies of patients with colorectal cancer (CRC).
Bioinformatics students in Spain have developed a mobile app capable of detecting in a matter of seconds three of the world's most common causes of vision loss and blindness.
Plastics are a part of everyday life, and an increasingly concerning factor of global environmental pollution. They also have infiltrated our bodies as microparticles (MPs) and nanoparticles (NPs), found even in placentas supporting foetal life. And they are in our blood. Now, researchers in Spain have developed a new method to detect and measure nanoparticles in human peripheral blood that is…
LLM-based generative chat tools such as ChatGPT or Google’s MedPaLM have great medical potential, but there are inherent risks associated with their unregulated use in healthcare.
Preterm birth affects nearly 10% of pregnancies worldwide, and rates are on the rise. A new approach that analyzes electrical activity during pregnancy, could improve predictions.
Autism spectrum disorder (ASD) is a developmental disorder associated with difficulties in interacting with others, repetitive behaviors, restricted interests and other symptoms that can impact academic or professional performance.
Messenger Ribonucleic Acid (mRNA) as a therapeutic approach is gaining momentum due to its ability to be rapidly manufactured and its promising outcomes.
Researchers from Queensland have developed a new fMRI technique with vastly increased temporal resolutions, enabling them to capture the dynamics of brain activity at a sub-second level.
The distinction between primary tumors and metastases can be made quickly and accurately in brain tumors using radiomics and deep learning algorithms, a new study shows.
AI-based models for multimodality hybrid imaging have the potential to be a potent clinical tool but are currently held back by a lack of transparency and maturity, says Dr Irène Buvat, from the Laboratory of translational Imaging in Oncology, Institute Curie in Paris, France.
Researchers from the University of Jyväskylä and the Central Finland Health Care District have developed an AI based neural network to detect an early knee osteoarthritis from x-ray images.
A new study demonstrates that AI models, using symptom and demographic features, can help predict Covid-19 infections, providing a way for rapid screening and cost-effective infection detection.
Reseachers from the University of Science and Technology of China have developed a method for contactless electrocardiogram (ECG) monitoring through a millimeter-wave radar system.
In surgery, artificial intelligence (AI) is applied mostly in imaging, navigation, and robotic intervention. However, AI can also play a major role in preoperative planning. Objective decisions-making, optimal utilisation of operating theatres and less overtime are additional advantages that are achieved with the use of AI in surgery.
Renal cell carcinoma is among the fifteen most common cancers worldwide. Dr Titus Brinker, from the German Cancer Research Center (DKFZ), looked at whether a convolutional neural network (CNN) can extract relevant image features from a typical H&E-stained slide to predict 5-year overall survival.
Deaths from cancer are currently estimated at 10 million each year worldwide. Conventional cancer staging systems aim to categorize patients into different groups with distinct outcomes. ‘However, even within a specific stage, there is often substantial variation in patient outcomes,’ Markus Plass, academic researcher from the Medical University of Graz, Austria, explained to Healthcare in…
Artificial intelligence (AI) can be used to detect COVID-19 infection in people’s voices by means of a mobile phone app, according to research to be presented at the European Respiratory Society International Congress.
Cardisiography is a screening method for detecting structural, rhythmical, or vascular heart disease and a decision support tool to guide targeted follow-up. Meik Baumeister, CEO of Cardisio, talks about the development and the operating principle.
A device with the appearance of a Wi-Fi router uses a neural network to discern the presence and severity of one of the fastest-growing neurological diseases in the world: Parkinson's.
An artificial intelligence (AI) model combining four methods of machine learning (ML) to accurately detect thyroid cancer from routine ultrasound image data has been developed by US researchers.
An algorithm built to assess scar patterns in patient heart tissue can predict potentially life-threatening arrhythmias more accurately than doctors can.
A software based on deep learning with convolutional neural networks can accurately and consistently classify breast density on mammograms according to BI-RADS criteria.
Using a novel probe for functional magnetic resonance imaging, researchers have devised a way to monitor individual populations of neurons and reveal how they interact with each other.
Combining questions about a person's health with data from smartwatch sensors, a new app can predict within minutes whether someone is infected with COVID-19.
The tool has made it possible to detect SARS-CoV-2 in exudate from symptomatic patients with a sensitivity of 100% and a specificity of 87.5%
Connecting the brain with a machine has been a powerful dream of mankind. What used to be science fiction, from the Borg in Star Trek to the Matrix, has become mainstream thanks to Elon Musk and Mark Zuckerberg who have put their entrepreneurial commitments into the area of neurotechnology. Recently, Professor Surjo R. Soekadar outlined current and upcoming applications of brain-computer…
A 'new technology shows promise by analyzing images of suspicious-looking lesions and quickly producing a detailed, microscopic image of the skin, bypassing several standard steps typically used for diagnosis - including skin biopsy, tissue fixation, processing, sectioning and histochemical staining.
Considerable advances in point-of-care testing (POCT) devices are emerging from lab-on-a-chip platforms, innovations in smartphone-based technology and wearable technology. Cloud-based deep learning systems herald a future revolution.
"Virtual Care & Digital Therapeutics", "Medical Artificial Intelligence & Robotics", "Fields of Innovation" and "Societal aspects of digitized healthcare" are the topics of this year's Health IT Forum at Medica. New this year: In line with the hybrid event concept of the trade fair, the Expert Panels, Tech Talks and Deep Dive Sessions can be…
Researchers have leveraged the power of digital pathology and computational modeling to detect and quantify podocytes, a specialized type of cell in the kidney that undergoes damaging changes during early-stage kidney disease.
Researchers at the national research institute for mathematics and computer science in the Netherlands (CWI), together with a colleague from Stichting Interuniversitair Micro-Elektronica Centrum (IMEC) in Eindhoven, have achieved a mathematical breakthrough in the computation of so-called spiking neural networks. Thanks to this breakthrough, special chips that are suitable for this artificial…
Researchers at the Skolkovo Institute of Science and Technology (Skoltech) led by Professor Dylov and their colleagues from First Pavlov State Medical University of St. Petersburg, Russia, have developed a brand-new approach to the task of 3D image segmentation — figuring out the contours of the constituent parts in a complex structure. While their so-called negative volume segmentation…
Machine learning methods are being used to predict the health of the placenta from a 30-second MRI scan. Researchers hope the approach will offer an insight into the health of expectant mothers and unborn babies by detecting the early signs of dangerous conditions such as pre-eclampsia. Researchers from the School of Biomedical Engineering & Imaging Sciences at King’s College London (KCL)…
The role of Artificial Intelligence (AI) is one of the most divisive issues in cardiology. Two leading experts argue the pros and cons of its use, exploring its benefits and advantages to cardiac care, as well as highlighting the pitfalls and shortcomings of AI, while underlining the need for clear guidelines and regulations for its use going forward.
Scientists use super-resolution microscopy to study previously undiscovered cellular worlds, revealing nanometer-scale details inside cells. This method revolutionized light microscopy and earned its inventors the 2014 Nobel Prize in Chemistry. In an international collaboration, AI researchers from Tübingen have now developed an algorithm that significantly accelerates this technology.
When patients undergo an MRI, they are told to lie still because even the slightest movement compromises the quality of the images and can create blurred spots and speckles known as artifacts. Moreover, a long acquisition time is usually required to provide high-quality MRI images. A team of researchers from Washington University in St. Louis has found a new deep learning method that can minimize…
Coronary computed tomography angiography (CCTA) is a non-invasive imaging test which can be used to evaluate coronary artery stenosis and measure plaques. Current plaque analysis is time-consuming and needs expert readers in order to help assess a patient’s heart attack risk. That’s about to change.
Artificial Intelligence (AI) is providing numerous opportunities across clinical care in the field of cardiovascular imaging. While challenges remain, AI is being applied in terms of diagnosis and prognosis, defining cardiovascular imaging pathways, and image acquisition and analysis. It can also help cardiologists predict which patients may do well, or which treatments are best applied to those…
Artificial intelligence (AI) will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that diseases can be detected at a very early stage based on subtle changes. However, implanting AI within the human body is still a major technical challenge. TU Dresden scientists at the Chair of…
An EPFL scientist has found that brain fingerprints – or maps of the neural connections within our brain – can be used to detect a decline in cognitive ability. That’s because the fingerprints are harder to detect in people who already have mild cognitive impairment.
A team of scientists at Argonne National Laboratory has leveraged artificial intelligence to train computers to keep up with the massive amounts of X-ray data taken at the Advanced Photon Source.
Artificial intelligence (AI) could match the impact of PACS on radiology. Covid-19 stimulated the development and testing of AI diagnostic-aiding tools in radiology, an unintended consequence of the pandemic. More image data sets have been created to train AI software – an unexpected benefit for radiology research.
A student team at Eindhoven University of Technology (TU/e) has introduced an interactive drone that guides elderly people to the exit during a fire in a nursing home, even before the fire brigade arrives. The Blue Jay Aeden is said to be the first interactive drone in the world that can transmit emotions and can fulfil an important function in saving people's lives.
Computer models have been standard tools in basic biomedical research for many years. However, around 70 years after the first publication of an ion current model of a nerve cell by Hodgkin & Huxley in 1952, researchers at Graz University of Technology (TU Graz), in collaboration with the Medical University of Graz and the Memorial Sloan Kettering Cancer Center in New York, have finally…
In noisy environments, it is difficult for hearing aid or hearing implant users to understand their conversational partner because current audio processors still have difficulty focusing on specific sound sources. In a feasibility study, researchers from the Hearing Research Laboratory at the University of Bern and the Inselspital are now suggesting that artificial intelligence (AI) could solve…
When viruses infect cells, changes in the cell nucleus occur, and these can be observed through fluorescence microscopy. Using fluoresence images from live cells, researchers at the University of Zurich have trained an artificial neural network to reliably recognize cells that are infected by adenoviruses or herpes viruses. The procedure also identifies severe acute infections at an early stage.
Dr. Hayder Amin and Dr. Caghan Kizil from the DZNE’s Dresden site aim to speed up developing drugs against brain diseases through cutting-edge technology. To this end, they are generating an innovative technology platform, termed “i3D-Markers”, based on high-density microelectrode arrays and 3-dimensional networks of human neurons. Compounds to be tested will be dripped onto this setup, and…
University of Washington researchers have discovered that AI models—like humans—have a tendency to look for shortcuts. In the case of AI-assisted disease detection, these shortcuts could lead to diagnostic errors if deployed in clinical settings.
Two clusters of brain cells compete to promote either the persistence or disappearance of traumatic memories, according to a new study conducted in mice. The findings could provide important insights into human conditions such as post-traumatic stress disorder (PTSD), anxiety disorders, and associated problems such as alcohol use disorder (AUD) that can arise from the persistence of traumatic…
Physicians are increasingly using software to automatically evaluate Holter ECG signals in adult patients, but so far, no software has been developed for children. Cardiomatics and the Medical University of Warsaw are on the way to a breakthrough in paediatric cardiology. They are developing an international tool for automatic assessment, analysis, and interpretation of electrocardiographic…
An artificial intelligence (AI)-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a new study. “There are an increasing number of MRIs that are performed, not only in the hospital but also for outpatients, so there is a real need to improve radiology workflow,” said study co-lead author Romane Gauriau, PhD,…
Researchers from Charité – Universitätsmedizin Berlin and the Francis Crick Institute have developed a mass spectrometry-based technique capable of measuring samples containing thousands of proteins within just a few minutes. It is faster and cheaper than a conventional blood count. To demonstrate the technique’s potential, the researchers used blood plasma collected from Covid-19 patients.…
From swallowing pills to injecting insulin, patients frequently administer their own medication. But they don’t always get it right. Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually. Researchers at the Massachusetts Institute of Technology (MIT) have developed a system to reduce those numbers for some…
Using a nanopore, researchers have demonstrated the potential to reduce the time required for sequencing a glycosaminoglycan — a class of long chain-linked sugar molecules as important to our biology as DNA — from years to minutes. Research to be published this week in the Proceedings of the National Academies of Sciences shows that machine-learning and image recognition software could be…
Doctors and healthcare workers may one day use a machine learning model, called deep learning, to guide their treatment decisions for lung cancer patients, according to a team of Penn State Great Valley researchers. In a study, the researchers report that they developed a deep learning model that, in certain conditions, was more than 71% accurate in predicting survival expectancy of lung cancer…
Artificial intelligence (AI) image reconstruction dramatically reduces magnetic resonance imaging (MRI) scan time, according to new research. The first clinical study comparing AI-accelerated knee MRI scans with conventional scans shows that the AI scans are not only diagnostically interchangeable with conventional ones, but also produce higher quality images. Results of this interchangeability…
To quickly and correctly diagnose diseases, medical professionals depend on identifying what biochemicals are present in tissue sections, where the biomolecules are, and at what concentrations. Mass spectrometry imaging—which can identify multiple biochemicals in a single experiment—is a promising technique to achieve this.
Predicting cancer outcome could help with a clinical decision regarding a patient’s treatment. In his keynote speech during the online ‘7th Digital Pathology and AI Congress: Europe’, Johan Lundin, Research Director at the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki and Professor of Medical Technology at Karolinska Institute, discussed ‘Outcome and…
A deep learning model to predict RNA-Seq expression of tumours from whole slide images was among the industry innovations outlined at the 7th Digital Pathology and AI Congress for Europe. Created by French-American start-up Owkin, the detail of how the company’s HE2RNA model provides virtual spatialization of gene expression was detailed to online delegates by senior translational scientist…
A panel of experts from the USA and China highlighted AI use in radiological workflow during the Covid pandemic and identified current pitfalls during the Hot Topic session at RSNA 2020. Radiologists from the USA prioritised Covid articles, delivered quick reviews, made all results open access, and helped organise a white paper from the Fleischner Society recognising recommendations for the role…
RSNA 2020: International experts showcased new studies on chest CT’s role in Covid-19 diagnosis and treatment. A staggering volume of work and has been produced on the pandemic this year, with an average 367 Covid-19 journal articles published per week, according to Michael Chung, Assistant professor of radiology at Icahn School of Medicine at Mount Sinai, NYC.
Low, light and with a field strength: 0.55-tesla with added new digital technologies. Indeed, this is a very new class of MRI scanner created by Siemens Healthineers. We interviewed Christiane Bernhardt, Vice President of Magnetic Resonance Marketing & Sales, Business Line MR, at Siemens Healthineers, about the technologies behind this development, plus its advantages and applications.
With its Magnetom Free.Max, Siemens Healthineers is presenting a new class of magnetic resonance imaging (MRI) systems that the company calls “High-V MRI.” The scanner’s unique combination of digital technologies and the new field strength of 0.55 tesla broadens the range of clinical applications for MRI systems. Magnetom Free.Max considerably improves pulmonary imaging with MRI and allows…
In the first study of its kind in cancer, researchers have applied artificial intelligence to measure the amount of muscle in patients with brain tumours to help improve prognosis and treatment.
The field of AI-enhanced imaging provides radiologists with an unprecedented opportunity to shape patient care, leading Austrian radiologist Katja Pinker-Domenig explained at ECR 2020.
Olympus Corporation announced the launch of Endo-Aid, a platform powered by artificial intelligence (AI) that includes the endoscopy application Endo-Aid CADe (computer-aided detection) for the colon. This new AI platform enables real-time display of automatically detected suspicious lesions and works in combination with Olympus’ recently introduced EVIS X1, its most advanced endoscopy system…
Focused ultrasound waves help researchers at ETH Zurich to deliver drugs to the brain only to where their effect is desired. This method is set to enable treatment of psychiatric and neurological disorders and tumours with fewer side effects in the future.
Scientists from Texas A&M University, Hewlett Packard Labs and Stanford University have developed a new nanodevice that acts almost identically to a brain cell.
Artificial intelligence (AI) experts at the University of Massachusetts Amherst and the Baylor College of Medicine report that they have successfully addressed what they call a “major, long-standing obstacle to increasing AI capabilities” by drawing inspiration from a human brain memory mechanism known as “replay.” First author and postdoctoral researcher Gido van de Ven and principal…
Value-based healthcare is gaining momentum and radiologists must increasingly show their contribution in improving patient care. Artificial intelligence (AI) can help them to do so and brings a series of new opportunities, according to Charles E Kahn, Professor and Vice Chairman of Radiology at the University of Pennsylvania, speaking at a meeting in Madrid in January. AI can do a lot to improve…
Neuroradiologist Dr Sofie Van Cauter described the challenges to brain tumour image segmentation during the European Society of Medical Imaging Informatics (EuSoMII) annual meeting in Valencia. She also outlined how, when clinically validated, AI could help tackle such problems. The WHO classification of brain tumours has come a long way since first introduced in 1979. The 2016 classification was…
The Center for Noise and Vibration Control at the Korea Advanced Institute of Science and Technology (KAIST) announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis. Professor…
Researchers at the University of Notre Dame are developing a new technique using artificial intelligence (AI) that would improve CT screening to more quickly identify patients with the coronavirus. The new technique will reduce the burden on the radiologists tasked with screening each image. Testing challenges have led to an influx of patients hospitalized with COVID-19 requiring CT scans which…
Patient data are a treasure trove for AI researchers. There’s a problem though: many algorithms used to mine patient data act as black boxes, which makes their predictions often hard to interpret for doctors. Researchers from Eindhoven University of Technology (TU/e) and the Zhejiang University in China have now developed an algorithm that not only predicts hospital readmissions of heart…
The ability of the human brain to process and store information is determined to a large extent by the connectivity between nerve cells. Chemical synapses are very important in this context as they constitute the interface for the transmission of information between individual nerve cells. Abnormalities in the formation of synapses cause many neurological disorders such as autism. Neurobiologists…
Canon Medical Systems USA, Inc. has received 510(k) clearance on its Advanced intelligent Clear-IQ Engine (AiCE) for the Vantage Orian 1.5T MR system, continuing to expand access to its new Deep Learning Reconstruction (DLR) technology. This technology, which is also available on the Vantage Galan 3T MR system and across a majority of Canon Medical’s CT product portfolio, uses a deep learning…
Luis Martí-Bonmatí, Director of the Medical Imaging Department at La Fe Hospital in Valencia, highlighted the need to assess utility when developing AI tools during ECR 2020. Artificial intelligence (AI) can impact and improve many aspects of clinical practice. But current expectations are too great and need to be toned down by looking at opportunities.
To investigate rare diseases, applying image-based analytics approaches, including the use of deep learning convolutional neural networks (DL-CNNs), can be a major challenge due to great difficulties in acquiring sufficient numbers of cases and associated digital image sets from the small cohorts typically available. To realise algorithms that are both effective and generalisable, conventional…
Understanding the source and network of signals as the brain functions is a central goal of brain research. Now, Carnegie Mellon engineers have created a system for high-density EEG imaging of the origin and path of normal and abnormal brain signals.
Scientists in the life sciences can now benefit from upgrades to a suite of analytical software solutions with new features designed to enhance productivity, confidence and accuracy in numerous fields, including proteomics, food safety and biotherapeutic drug development. The latest suite of software strengthens laboratory workflows across a range of applications through expanded capabilities,…
Tissue biopsy slides stained using hematoxylin and eosin (H&E) dyes are a cornerstone of histopathology, especially for pathologists needing to diagnose and determine the stage of cancers. A research team led by MIT scientists at the Media Lab, in collaboration with clinicians at Stanford University School of Medicine and Harvard Medical School, now shows that digital scans of these biopsy…
Researchers have developed an AI algorithm that can detect and identify different types of brain injuries. The researchers, from the University of Cambridge and Imperial College London, have clinically validated and tested the AI on large sets of CT scans and found that it was successfully able to detect, segment, quantify and differentiate different types of brain lesions. Their results,…
Machine learning and AI are highly unstable in medical image reconstruction, and may lead to false positives and false negatives, a new study suggests. A team of researchers, led by the University of Cambridge and Simon Fraser University, designed a series of tests for medical image reconstruction algorithms based on AI and deep learning, and found that these techniques result in myriad…
Bringing molecular and digital pathology closer together through a more integrative approach can lead to clear advantages for diagnostic and research workflows. During the recent Digital Pathology and AI Congress (London), Professor Viktor Koelzer explored the benefits and paid particular attention to colorectal cancer (CRC).
Artificial intelligence (AI) may be an aid to interpreting ECG results, helping healthcare staff to diagnose diseases that affect the heart. Researchers at Uppsala University and heart specialists in Brazil have developed an AI that automatically diagnoses atrial fibrillation and five other common ECG abnormalities just as well as a cardiologist. The study has been published in Nature…
University of Massachusetts Amherst researchers have invented a portable surveillance device powered by machine learning – called FluSense – which can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses and influenza trends. The FluSense creators say the new edge-computing platform, envisioned for use in hospitals, healthcare waiting rooms…
Researchers at Linköping University (LiU) have developed an algorithm that can identify patients at a higher risk of septic shock, a life-threatening condition that is difficult for doctors to predict. At the same time, it is important to recognise the symptoms as early as possible, since early treatment increases the chance of survival. A group of LiU researchers is using artificial…
A deep learning method with a convolutional neural network (CNN) can support the evaluation of small solid renal masses in dynamic CT images with acceptable diagnostic performance, according to an article published ahead-of-print in the March issue of the American Journal of Roentgenology (AJR). Between 2012 and 2016, researchers at Japan’s Okayama University studied 1807 image sets from 168…
Researchers at Osaka University have developed a computer method that uses magnetic resonance imaging (MRI) and machine learning to rapidly forecast genetic mutations in glioma tumors, which occur in the brain or spine. The work may help glioma patients to receive more suitable treatment faster, giving better outcomes. The research was recently published in Scientific Reports. Cancer treatment…
A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors, a new study finds. Published in Nature Medicine, the study examined the diagnostic accuracy of brain tumor image classification through machine learning, compared with the accuracy of pathologist interpretation of conventional…
Bringing the power of AI to routine imaging, Advanced intelligent Clear-IQ Engine (AiCE), Canon Medical’s Deep Learning Reconstruction (DLR) technology, is now being integrated across a broader portfolio of scanners with a wider range of clinical applications across modalities. Advanced intelligent Clear-IQ Engine (AiCE) was trained using vast amounts of high-quality image data, and features a…
At RSNA 2019, GE Healthcare launches more than 30 new, imaging intelligent applications and smart devices designed to drive efficiency in radiology departments, aiming to double productivity and cost savings for systems by 2025. For healthcare executives, the new offerings help systems to save costs, improve technology utilization, and increase patient volumes. Clinicians also will benefit from…
September: Basel, Switzerland: ‘Intelligent Health 2019’, a conference dedicated to artificial intelligence (AI) in medicine, underlined the growing interest by the rising number of attendees – 1,400 in 2018, its first year, to 2,027 this year. With examples of AI use from around the world, the common thread throughout was how AI can serve humankind by enabling better understanding of…
For the first time, researchers from Helmholtz Zentrum München and the University Hospital of LMU Munich show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia (AML). Their proof of concept study paves the way for an automated, standardized and on-hand sample analysis in the near future. The paper was…
Although some people foresee artificial intelligence (AI) easing medical workloads, many challenges arise before that dream can begin. Dr Felix Nensa and Dr Bram Stieltjes described such hurdles in a session held during a SITEM School Symposium in Bern, Switzerland. Whilst AI has potential, actually delivering that asset in to routine medical practice remains a major challenge.
Scientists at ETH Zurich and the University of Zurich have used machine learning methods to improve optoacoustic imaging. This relatively young medical imaging technique can be used for applications such as visualizing blood vessels, studying brain activity, characterizing skin lesions and diagnosing breast cancer. However, quality of the rendered images is very dependent on the number and…
As a member of the European Congress of Radiology (ECR) planning committee Professor Elmar Kotter suffered no serious challenge in pinpointing subject matter for the IT sessions. More than 300 submissions were received on artificial intelligence (AI). From the presentations, Kotter, Professor of Radiology and Senior Consultant at the Clinic for Diagnostic and Interventional Radiology, at the…
Researchers have developed a neural network approach that can accurately identify congestive heart failure with 100% accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat, a new study reports. Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and…
Uwe Joseph Schoepf, Professor for Radiology, Cardiology and Paediatrics and Director of the Department of Cardiovascular Imaging at the Medical University of South Carolina, discusses areas of application for AI-based radiology. The cardiothoracic imaging expert and his team were largely involved in the development and early clinical trials of the Siemens AI-Rad Companion Chest CT, a software…
The School for Translational Medicine and Biomedical Entrepreneurship (sitem-insel School) in Bern, Switzerland, offers a new Certificate of Advanced Studies (CAS) in Artificial Intelligence in Medical Imaging. The course aims to equip Medical Doctors (MDs) with the necessary skills to take a leading role in the AI-driven transformation of medicine. The course program was developed for medical…
Scientists have identified mechanisms in the human brain that could help explain the phenomenon of the 'Uncanny Valley' - the unsettling feeling we get from robots and virtual agents that are too human-like. They have also shown that some people respond more adversely to human-like agents than others.
Epilepsy affects around 70 million people worldwide, making it the second most common neurological disorder after migraine. Epileptics bear a terrible burden because they experience recurrent seizures that strike without warning. Their symptoms range from brief suspension of awareness to violent convulsions and sometimes loss of consciousness. Epilepsy is also responsible for numerous deaths –…
As reporting workload for pathology departments continues to rise rapidly, artificial Intelligence (AI) solutions are set to play an increasing role in daily practice. ‘I see this as the future of digital pathology,’ said histopathologist Professor David Snead at the Digital Pathology and Artificial Intelligence Congress held in London.
In a clinical trial of 220 people with “wet” age-related macular degeneration, Johns Hopkins Medicine researchers, collaborators from many sites across the country, and Genentech in South San Francisco have added to evidence that using a new implant technology that continuously delivers medication into the eyes is safe and effective in helping maintain vision and reduces the need for…
Using artificial intelligence (AI) to push development of imaging biomarkers shows great promise to improve disease understanding. This alliance could be a game changer in healthcare but, to advance research, clinical validation and variability of results must be factored in, a prominent Spanish radiologist advises. In clinical practice efforts are already ongoing to apply AI to obtain new…
Spanish healthcare AI company QUIBIM announced that its AI-powered Chest X-Ray Classification tool has received CE certification. The company already obtained the class IIa CE mark earlier this year for the imaging biomarker analysis algorithms, the zero footprint DICOM viewer and the platform within the QUIBIM Precision platform, becoming the first Spanish firm to ever receive the clearance.
Hackers can access a patient's 3-D medical scans to add or remove images of malignant tumors, thus placing patients at risk of misdiagnoses. The new study, published by Ben-Gurion University of the Negev cybersecurity researchers, showed that the altered scans successfully deceived both radiologists and artificial intelligence algorithms used to aid diagnosis. A 3-D CT (computerized…
AI has made an extraordinary qualitative jump, particularly in machine learning. This can help quantify imaging data to tremendously advance both pathology and radiology. At a recent meeting in Valencia, delegates glimpsed what quantitative tools can bring to medical imaging, as leading Spanish researcher Ángel Alberich-Bayarri from imaging biomarker company Quibim unveiled part of his work.
Professor Christoph M Friedrich researches the interface between man and molecule. Born in Westphalia, Germany, the professor for biomedical computer science at Dortmund University of Applied Sciences recently took up an additional role at the Institute for Medical Informatics, Biometrics and Epidemiology (IMIBE) in Essen University Hospital. In 2013, the cooperation between the two institutions…
Researchers are using artificial intelligence to reduce the dose of contrast agents like Gadolinium that may be left behind in the body after MRI exams, according to a study presented at the annual meeting of the Radiological Society of North America (RSNA).
A world where machines can be controlled by thought alone – such is the promise of so-called brain-computer interfaces (BCI). BCIs are both hardware and software communication systems that read brain and nerve signals, convert those into electrical signals and translate human thoughts into machine commands. Developers of BCIs rely on artificial intelligence, neural network models and big data…
A deep neural network algorithm called BOTA uses bacterial genomes to identify unrecognized bacterial antigens.
Imec, the world-leading research and innovation hub in nanoelectronics and digital technologies, released and is making available its state-of-the-art high-density neural probe, Neuropixels, to the global neuroscience research community. With almost a thousand electrodes, and 384 recording channels on a single shank, the Neuropixels probe provides an unprecedented resolution for mapping brain…
Standardised and well-structured data, as well as the definition of clear objectives, are indispensable prerequisites for artificial intelligence implementation into clinical processes. ‘Ask not what artificial intelligence can do for you but what you can do for artificial intelligence!’ This variation on John F Kennedy’s famous quote comes from Dr Ben Glocker, Senior Lecturer in Medical…
'Image Computing, including image analysis, artificial intelligence, artificial neural networks und deep learning, is starting a revolution,’ says Dr Paul Suetens, professor of Medical Imaging and Image Processing at University Hospital Leuven. Artificial Intelligence (AI) is not new – research in this field was carried out as far back as the 1950s – but, whilst in the early days AI learnt…
Machine learning is increasingly helping radiologists to acquire faster and better quality images, and measure heart function. This is just the tip of the iceberg; artificial intelligence has far more to bring to the heart, explained Daniel Rueckert, Head of the Department of Computing at Imperial College London, during CMR 2018. Machine learning (ML) is becoming a valuable assistant for…
Everyone knows what our brains look like – but why is it folded up like that? Looking at other species reveals much less folding or even none at all. Scientists in Dresden, Germany, have now taken a closer look at the ridges and grooves of human brains. They discovered what causes our brains to fold – and what happens when the folding process goes wrong.
SLAC and Stanford researchers are developing a device that combines electrical brain stimulation with EEG recording, opening potential new paths for treating neurological disorders. It could help bring back lost brain function by measuring how the brain responds to therapies that stimulate it with electric current.
Biomedical engineers at Columbia Engineering have discovered a new fundamental feature of brain oscillations: they actually move rhythmically across the brain, reflecting patterns of neuronal activity that propagate across the cortex. The coordination of neural activity across widespread brain networks is essential for human cognition. Researchers have long assumed that oscillations in the brain,…
Researchers have shown for the first time that a form of artificial intelligence or machine learning known as a deep learning convolutional neural network (CNN) is better than experienced dermatologists at detecting skin cancer. In a study published in the leading cancer journal Annals of Oncology, researchers in Germany, the USA and France trained a CNN to identify skin cancer by showing it more…
AI-based applications will replace radiologists in some areas, the physicist Bram van Ginneken predicts. ‘The profession of radiologist will change profoundly,’ predicts Gram van Ginneken, Professor of Medical Image Analysis at Radboud University Medical Centre. The cause is automatic image analysis by computers (first published in a paper in 1963) and deep learning.
Ever get chills listening to a particularly moving piece of music? You can thank the salience network of the brain for that emotional joint. Surprisingly, this region also remains an island of remembrance that is spared from the ravages of Alzheimer’s disease. Researchers at the University of Utah Health are looking to this region of the brain to develop music-based treatments to help alleviate…
Population imaging is key to determining disease prediction and risk prevention, and Big Data will be key to extracting information and drawing analysis from imaging results, experts highlighted during the annual meeting of the European Society of Magnetic Resonance in Medicine and Biology (ESMRMB) held in Barcelona in October. Interest in cohort studies has been increasing over the years and…
In the next five to 10 years, artificial intelligence is likely to fundamentally transform diagnostic imaging. This will by no means replace radiologists, but rather help to meet the rising demand for imaging examinations, prevent diagnostic errors, and enable sustained productivity increases.
The New Horizons Lecture at the RSNA annual meeting is a keynote address that looks to the future, and the inventor of a major innovation in magnetic resonance imaging (MRI) technology, Daniel K Sodickson MD PhD, did just that. His lecture entitled ‘A New Light: The Birth and Rebirth of Imaging’ looked back at how MRI has evolved and forward at what it will become.
Some time in the distant future artificial intelligence (AI) systems may displace radiologists and many other medical specialists. However, in a far more realistic future AI tools will assist radiologists by performing very complex functions with medical imaging data that are impossible or unfeasible today, according to a presentation at the RSNA/AAPM Symposium during the Radiological Society of…
Researchers used machine learning techniques, including natural language processing algorithms, to identify clinical concepts in radiologist reports for CT scans, according to a study conducted at the Icahn School of Medicine at Mount Sinai and published in the journal Radiology. The technology is an important first step in the development of artificial intelligence that could interpret scans and…
Machine learning is playing an increasing role in computer-aided diagnosis, and Big Data is beginning to penetrate oncological imaging. However, some time may pass before it truly impacts on clinical practice, according to leading UK-based German researcher Professor Julia Schnabel, who spoke during the last ESMRMB annual meeting. Machine learning techniques are starting to reach levels of human…
Lawrence Livermore National Laboratory scientists and engineers have developed a “brain-on-a-chip” device aimed at testing and predicting the effects of biological and chemical agents, disease, or pharmaceutical drugs on the brain over time without the need for human or animal subjects. The device, part of the Lab’s iCHIP (in-vitro Chip-Based Human Investigational Platform) project,…
The use of deep learning (DL) technology could help radiologists increase the quality of breast cancer screening programs, lower costs, and reduce the variability in the cancer detection process. And the role of DL technology in imaging doesn't stop there. In fact, it is likely that DL computers can be trained to read mammograms as well as radiologists and — in the future — maybe even…
Automation might be the solution for many of the challenges radiologists and clinicians face today. Toshiba Medical, a Canon Group, is currently pushing the boundaries of what automation can accomplish and presenting their project in progress at this year's RSNA. Overwhelming volume of clinical data every day, limited access to relevant clinical information, missed findings and lack of…
GE Healthcare and NVIDIA announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500,000 imaging devices globally and accelerate the speed at which healthcare data can be processed. The scope of the partnership, detailed at the 103rd annual meeting of the Radiological Society of North America (RSNA), includes the…
In the nineties Deep Blue, the famous chess computer, defeated Kasparow. Only a year ago Google’s Deepmind managed to master the ancient Chinese Go, known for its utmost complexity.
Columbia Engineers make major advance in helping the hearing impaired follow a conversation in a noisy environment - and bring cognitive hearing aids a step closer to reality.
Approximately one percent of the world population are epileptic; in France alone, an estimated 600,000 people regularly experience seizures.
Autonomous driving, automatic speech recognition, and the game Go: Deep Learning is generating more and more public awareness. Scientists at the Helmholtz Zentrum München and their partners at ETH Zurich and the Technical University of Munich (TUM) have now used it to determine the development of hematopoietic stem cells in advance. In ‘Nature Methods’ they describe how their software…
New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain.
Tufts University researchers have discovered a new technique for generating rapidly-differentiating human neural stem cells for use in a variety of tissue engineering applications, including a three-dimensional model of the human brain, according to a paper published in Stem Cell Reports. The work could pave the way for experiments that engineer other innervated tissues, such as the skin and…
Pathologists have been largely diagnosing disease the same way for the past 100 years, by manually reviewing images under a microscope. But new work suggests that computers can help doctors improve accuracy and significantly change the way cancer and other diseases are diagnosed. A research team from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School (HMS) recently developed…
Knowledge modules, speech interfaces, robotics, analytics, and the Internet of Things demonstrate advances in intelligent computing in industries such as transportation, retail, and financial services. What role have they taken on the healthcare stage?
MRI, CT, pathology: doctors have to consider medical image data – increasing in both amount and complexity – to perform diagnoses and monitor therapy. The Fraunhofer Institute for Medical Image Computing MEVIS in Bremen is creating a new approach to provide effective assistance.
Bioengineers and cognitive scientists have developed the first portable, 64-channel wearable brain activity monitoring system that’s comparable to state-of-the-art equipment found in research laboratories.
Juries in criminal cases typically decide if someone is guilty, then a judge determines a suitable level of punishment. New research confirms that these two separate assessments of guilt and punishment – though related - are calculated in different parts of the brain. In fact, researchers found that they can disrupt and change one decision without affecting the other.
A study three years ago sparked a medical mystery when it revealed a part of the brain not found in any present-day anatomy textbooks. Recently, Indiana University computational neuroscientist Franco Pestilli and an international research team published an article in the journal Cerebral Cortex that suggests this missing part of the brain may play an important role in how we understand the world…
Fructose not only results in a lower level of satiety, it also stimulates the reward system in the brain to a lesser degree than glucose. This may cause excessive consumption accompanied by effects that are a risk to health, report researchers from the University of Basel in a study published in the scientific journal PLOS ONE. Various diseases have been attributed to industrial fructose in…
A group of passengers who thought they were going to die when their plane ran out of fuel over the Atlantic Ocean in August, 2001 have had their brains scanned while recalling the terrifying moments to help science better understand trauma memories and how they are processed in the brain.
A new imaging technique can identify the specific changes in neural communication that can disrupt functional connectivity across the brain as a result of mild traumatic brain injury (mTBI).
The research objective of Dr.-Ing. Laura De Laporte, junior group leader at DWI – Leibniz Institute for Interactive Materials in Aachen, is to develop a minimally invasive therapy for spinal cord injury. Her goal and her scientific approach to develop an injectable material with the ability to provide biochemical and physical guidance for regenerating nerves across the injury site, was selected…
MAQUET and Swisstom are pleased to announce their distribution partnership for the monitoring and diagnostic product Swisstom BB2.
New insights into the ways the human brain functions – that is the promise of mapping the entire web of connections in the brain, the so-called connectome. New developments in connectome imaging are one of the major topics at this year’s European Congress of Radiology (ECR).
How do our brains combine information from the external world (sensory stimulation) with information on our internal state such as hunger, fear or stress?
‘We finally have tools to non-invasively study the human brain in normal subjects and diseased patients,’ says Professor Stefan Sunaert, Head of Translational MRI at the Department of Imaging & Pathology, Leuven University Hospital (Belgium)
“We finally have tools to non-invasively study the human brain in normal subjects and diseased patients,” says Professor Stefan Sunaert, Head of Translational MRI at the Department of Imaging & Pathology at Leuven University Hospital (Belgium).
An artificial “brain” built by a 17-year-old whiz kid from Florida is able to accurately assess tissue samples for signs of breast cancer, providing more confidence to a minimally invasive procedure. The cloud-based neural network took top prize in this year’s Google Science Fair.
Interfaces between the brain and electrical circuits in technical devices or computers open new perspectives for basic research and medical application, e.g., for therapeutic brain stimulation and neuroprosthetics. The new EU project CORONET will develop the technological and theoretical foundations for such future “bio-hybrid” interfaces between biological and artificial nervous tissues.
Big discussions are expected at the upcoming European Association of Urology (EAU) Congress in Stockholm* when urologist Dr Jochen Walz (right), of the Urological Department at the Institute Paoli-Calmettes, Marseilles, France, presents the forum: Imaging in Europe: Who, where, what, how many! and M F Coelho, of the European Society of Urological Imaging (ESUI) describes the Clinical utility of…
UK - A hand-sized, electronic peak flow meter, which measures lung capacity and can be connected to a PDA mobile handset is being tested for use by asthma sufferers.
Neural networks are emblematic of complex systems, so it's no surprise that the field of neurology is eclectic and intricate, too. Main challenges for neurologists are therapies of and research on stroke, seizures, movement disorders such as Parkinson's disease, autoimmune disorders such as multiple sclerosis and dementias such as Alzheimer's disease.
