Search for: "neural networks" - 143 articles found

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Article • BCI

Quantum sensors for next-gen brain-computer interfaces

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…

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News • ECG computation

Energy-efficient AI detects heart defects

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…

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News • Negative volume segmentation

Novel 3D image segmentation for literal ‘jaw-dropping’

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…

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Article • Pregnancy imaging

Machine learning predicts placenta health from MRI scans

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)…

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Article • Discussing benefits and flaws

AI in cardiology: a marriage made in heaven – or hell?

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.

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News • Biological image analysis

Machine learning accelerates super-resolution microscopy

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.

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News • Imaging assistance

Deep learning method boosts MRI results without new data

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…

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Article • Diagnosis, prognosis, prediction

AI offers advances in cardiovascular imaging

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…

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News • Early detection and treatment of illnesses

Researchers develop implantable AI system

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…

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Article • Heard at SIIM 2021

AI in radiology: unexpected benefits, unintended consequences

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.

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News • Panic prevention

Drone helps elderly escape from burning nursing homes

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.

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News • Promising research tool

World's first digital cancer cell model

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…

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News • Study on devices and implants

AI could improve speech recognition in hearing aids

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…

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News • AI-assisted analysis

Prediciting viral infections with microscopy & deep learning

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.

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News • Medication development platform

Smart biomarkers to find new drugs against brain diseases

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…

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News • Stress, depression, anxiety

Suppress or sustain? How our brain handles traumatic memories

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…

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News • Cardiology

On the way to better analysis of paediatric ECGs

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…

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News • Incidental findings identification

AI system for brain MRIs could boost workflows

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,…

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News • Mass spectrometry

"Protein fingerprint" rapidly identifies Covid-19 biomarkers

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.…

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News • Self-administration of medication

Many patients use their inhalers and insulin pens wrong. An AI system could fix this

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…

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News • Potential for rapid, accurate glycan sequencing

Enormous boost for sequencing key molecules

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…

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News • Survival prediction

Deep learning may lead to better lung cancer treatments

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…

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Article • 'Thumbs up' for image reconstruction

Facebook AI accelerates MRI exams

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…

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Article • AI use in clinical diagnosis

Deep learning tool predicts tumour expression from whole slide images

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…

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Article • Applications of machine learning

Training AI to predict outcomes for cancer patients

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…

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Article • USA and Chinese experts share observations

AI in Covid research

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…

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Article • The role of chest CT in diagnosis and treatment

UPDATE: Covid-19 and lung infections imaging

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.

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Sponsored • The most compact .55-T full body scanner

Lungs plus A&E MRI scans – no problem

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.

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News • Downsizing imaging

Siemens launches its smallest and most lightweight whole-body MRI

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…

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News • Computer-aided detection

Olympus launches AI-powered endoscopy platform

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…

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News • The network remembers

Brain-inspired memory abilities to make AI less 'forgetful'

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…

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Article • Improving the role of radiology

Value-based healthcare: AI reveals the bigger picture

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…

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Article • Neuro-oncology

Challenges in brain tumour segmentation

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…

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Video • Deep learning application

COVID-19 cough camera: device detects location of coughing sounds in real-time​

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…

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News • Improved accuracy and efficiency

AI could improve CT screening for COVID-19

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…

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News • Shedding light into the 'black box' of AI

Neural network helps explain relapses of heart failure patients

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…

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News • Neurology research

Calcium channel subunits play a major role in autistic disorders

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…

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News • Deep learning in imaging

1.5T MR system receives FDA clearance for AI-based image reconstruction technology

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…

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Article • Expectations vs. reality

AI in clinical practice: how far we are and how we can go further

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.

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Article • Digital pathology

VIPR: Deep learning for small cohorts

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…

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News • high-density EEG

A deeper look inside the brain

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.

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News • Sample analysis

Next-generation analytical lab software strengthens data exploration

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,…

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News • From physical to computational staining

Deep learning accurately stains digital biopsy H&E slides

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…

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News • Lesion differentiation

AI successfully identifies different types of brain injuries

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,…

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News • Algorithm-assisted diagnostics

AI in imaging: not as reliable as you'd think

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…

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Article • A more integrative approach to digital pathology

imCMS: The door to simple, cheap, reliable bio-stratification

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).

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News • ECG algorithm

New AI tool for cardiac diagnostics

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…

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News • Flu forecast

Portable AI device predicts outbreaks based on coughing

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…

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News • Decision support

AI can predict septic shock

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…

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News • Deep learning & CNN

Algorithm differentiates small renal masses on multiphase CT

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…

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News • MRI & machine learning

A look into the genome of brain tumors

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…

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News • Stimulated Raman histology

Imaging system and AI algorithm accurately identify brain tumors

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…

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News • Advancements in CT and MR

Canon expands the power of AI across imaging modalities

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…

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News • Smart devices and more

New GE imaging tech and intelligent apps unveiled at RSNA

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…

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Article • Impressive advances reported at Intelligent Health 2019

China pushes the use of medical AI

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…

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News • Deep learning vs. AML

AI-driven blood cell classification supports leukemia diagnosis

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…

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Article • Transferring research into daily routine

AI possibilities and probabilities

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.

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News • Better image quality with fewer sensors

Machine learning improves biomedical imaging

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…

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Article • Artificial intelligence

Superlative future assistance

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…

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News • Neural network approach to ECG

AI detects heart failure from a single heartbeat

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…

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Article • Cardiology & radiology

AI opens up boundaries between medical disciplines

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…

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News • CAS 'Artificial Intelligence in Medical imaging'

Advance your AI skills in Bern

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…

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Article • Predicting attacks with AI

Epilepsy: Seizure detection method brings hope

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 –…

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Article • Revolution through AI

Pixel analysis: the new era of digital pathology

As reporting workload for pathology departments continues to rise rapidly, artificial Intelligence solutions are set to play an increasing role in daily practice. In many pathology departments the annual number of cases has risen by around 2-4% but the slides produced has doubled in the last decade. Histopathologist Professor David Snead identified this phenomenon within his own centre in the…

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News • Macular Degeneration

Implanted drug ‘reservoir’ reduces injections

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…

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Article • Artificial Intelligence

Allying AI to biomarkers is powerful but validation remains challenging

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…

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News • Certification

AI-fueled chest x-ray classifier gets CE mark

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.

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Video • Cyberattack

Hackers can manipulate cancer scans

​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…

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Article • Image analysis in radiology and pathology

"The time has come" for AI

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 unveiled part of his work. The boom in companies and start-ups…

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Interview • Between man and molecule

The hunt for genetic risk factors

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…

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Article • Neuro-research

Brain-computer interfaces: Getting a Grasp on how we think

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…

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News • Neuroscience

"Neuropixels" neural probe to map brain activity

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…

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Article • AI structure

Machine Learning: into the pumpkin patch

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…

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Article • The revolution escalates

AI image analysis: Opportunity or threat?

'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…

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Article • A valuable assistant

AI will transform radiologists into data scientists

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…

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News • Neural development

Why our brains fold the way they do

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.

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News • Neurology

Waves move across the human brain to support memory

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,…

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News • Man against machine

AI is better than dermatologists at diagnosing skin cancer

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…

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Article • The impact of AI

Radiology and radiologists: a painful divorce

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.

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News • The power of sound

Music activates regions of the brain spared by Alzheimer’s disease

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…

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Sponsored • A discipline transforming

Adding value with AI in medical imaging

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.

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Article • The InnerEye Project

AI drives analysis of medical images

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…

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Article • An era of turbulence and innovation

The birth and rebirth of imaging

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.

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Article • Compelling cohorts

Population imaging: Big Data will boost disease prediction

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…

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Video • Automation in radiology

Machine learning techniques generate clinical labels of medical scans

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…

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Article • Smart techniques

Machine learning is starting to reach levels of human performance

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…

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News • Simulated CNS

This ‘brain-on-a-chip” could be a new medical testing ground

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,…

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News • A new chance for screening

Deep Learning shows potential for accurately reading mammograms

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…

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News • Work in Progress

Toshiba Medical pushes the boundaries of automation

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…

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News • Cooperation

GE and NVIDIA join forces to accelerate AI adoption in healthcare

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…

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News • Deep Learning

Deep Learning predicts hematopoietic stem cell development

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…

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News • For tissue engineering

Technique generates human neural stem cells

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…

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News • Breast cancer

Artificial intelligence diagnoses with high accuracy

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…

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News • Science

How the brain decides blame and punishment

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.

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News • Computational neuroscience

The lost highway in the brain

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…

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Fructose produces less rewarding sensations in brain

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…

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News • Neurology

Reliving nightmare flight offer new clues about trauma memory

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.

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Research on injectable oriented hydrogels for spinal cord repair

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…

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New EU project CORONET

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.

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EAU hot topic: Imaging in urological oncology today

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…

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Article • Information channel

Neurology: Let's get nervous

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.

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