#AI

Photo

Breast imaging

Hologic launches AI powered imaging technology

Hologic, Inc. announced the commercial availability in Europe of its 3DQuorum Imaging Technology, Powered by Genius AI. The innovation was designed to help improve mammography efficiency and workflow, which is critical as clinics strive to manage the backlog of women whose routine breast screening was delayed due to the COVID-19 lockdown.

Photo

Deep learning applied to MRI scans

Glioblastoma: Using AI to improve prognosis and treatment

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. Dr Ella Mi, a clinical research fellow at Imperial College London (UK) will tell the NCRI Virtual Showcase, that using deep learning to evaluate MRI brain scans of a muscle in the head was as accurate and…

Photo

Algorithms must meet quality criteria

Deep Learning in breast cancer detection

A French expert in breast imaging looked at the latest Deep Learning (DL) applications in her field, screening their strengths and weaknesses in improving breast cancer detection. It is really important to understand which types of data sets need to be checked when evaluating an AI model for image interpretation, according to Isabelle Thomassin-Naggara, Professor of Radiology at Sorbonne…

Photo

AI in clinical practice

Hospitals must think big, small and new

AI in healthcare has been a trending, sometimes head-spinning topic for a few years – and, with the COVID-19 pandemic, clinicians have been presented with a whole new range of AI products that may or may not meet their needs. When it comes to choosing one’s own set of tools, which criteria should prevail? A panel of European and US experts gave concrete examples of AI’s current…

Photo

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…

Photo

Unleashing the potential

AI increases colorectal polyp detection

An AI (Artificial Intelligence) assisted polyp detector is helping endoscopists find more lesions during colorectal examinations. Leading endoscopists highlighted how the system is improving performance and finding flat or hidden polyps that the human eye could miss, in a webinar entitled “Artificial Intelligence - How to unleash the potential for colorectal polyp detection.” Hosted by the…

Photo

Digitising healthcare

Virtual assistants and digital twins advance personalised medicine

Siri and Alexa are leading the way: the virtual assistants meet many daily needs. Soon, similarly programmed software and a ‘digital patient twin’, will be launched into the medical world – both IT applications based on Artificial Intelligence (AI). The virtual medical assistant and digital patient twin are two key aspects of a research project ‘Models for Personalised Medicine’.…

Photo

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…

Photo

Overcoming the barriers to AI in digital pathology

‘You can’t do AI on glass slides’

As Artificial Intelligence continues to impact on the development of digital pathology, potential users are still slow to implement key enabling technologies to harness the benefits, according to Dr David McClintock, who will detail critical steps for pathology departments to transition practice from glass (analogue) to digital (whole slide imaging) and embrace AI, to the 6th Digital Pathology…

Photo

Need for modernisation

Digital pathology: Luxury or necessity?

The anatomical pathologist faces a crisis. Public and private labs suffer increasing caseloads, whilst pathologist numbers diminish for various reasons, including greater cancer prevalence associated with aging populations as well as improved cancer screening programs. Precision medicine typically involves more genetic testing and extensive use of immunohistochemistry to classify cancer and…

Photo

Joint Research

AI helps diagnosing Covid-19

Fujitsu and Tokyo Shinagawa Hospital today announced the launch of a joint R&D project for AI technology to support diagnostic imaging via chest CT (Computed Tomography), which represents a promising candidate for the effective diagnosis of COVID-19 pneumonia.

Photo

Facial photo analysis

AI uses ‘selfies’ to detect heart disease

Sending a “selfie” to the doctor could be a cheap and simple way of detecting heart disease, according to the authors of a new study. The study is the first to show that it’s possible to use a deep learning computer algorithm to detect coronary artery disease (CAD) by analysing four photographs of a person’s face. Although the algorithm needs to be developed further and tested in larger…

Photo

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…

Photo

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…

Photo

Reducing coronavirus test burden

AI speeds up COVID-19 screening in emergency rooms

Researchers from Eindhoven University of Technology (TU/e) and the Catharina Hospital in Eindhoven have developed a new algorithm for the rapid screening for COVID-19. The software is intended for use in Emergency Rooms (ER), to quickly exclude the presence of corona in incoming patients. As a result, doctors need to conduct fewer standard coronavirus tests, increasing efficiency. The quick scan…

Photo

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…

Photo

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…

Photo

Imaging informatics meeting

SIIM 2020: Glancing back at 40 years and ahead to the future

Forty years ago, a group of visionaries who believed that computers would have a huge impact on the functions of radiology departments formed the Radiology Information System Consortium (RISC). In 1989, RISC created the Society for Computer Applications (SCAR) to promote computer applications in digital imaging, and these organizations ultimately evolved to become the Society for Imaging…

Photo

Smart breathing support

Self-learning ventilators could save more COVID-19 patients

As the corona pandemic continues, mechanical ventilators are vital for the survival of COVID-19 patients who cannot breathe on their own. One of the major challenges is tracking and controlling the pressure of the ventilators, to ensure patients get exactly the amount of air they need. Researchers at the Eindhoven University of Technology (TU/e) have developed a technique based on self-learning…

Photo

Future of contrast agents

Gadolinium in MRI is here to stay (at least for a while)

Manganese and iron oxide contrast agents can replace gadolinium-based contrast agents (GBCA) in a number of MRI examinations, but gadolinium remains a strong candidate when properly indicated, especially with AI-driven dose reduction and advances to increase relaxivity, a French expert explained at ECR 2020. GBCA have been MRI companions for many years. In France, 30% of all MR examinations are…

Photo

Going digital

How digital pathology is shaping the future of precision medicine

In recent years, technological and regulatory advances have made digital pathology a viable alternative to the conventional microscope. The obtention of a digital replica of the traditional glass slide and its use for primary diagnosis has revolutionized pathology and is shaping the future of the discipline. A digital pathology lab uses digital histology slides for routine diagnosis, and these…

Photo

Brain tumor treatment network

'Federated learning' AI approach allows hospitals to share patient data privately

To answer medical questions that can be applied to a wide patient population, machine learning models rely on large, diverse datasets from a variety of institutions. However, health systems and hospitals are often resistant to sharing patient data, due to legal, privacy, and cultural challenges. An emerging technique called federated learning is a solution to this dilemma, according to a study…

Photo

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…

207 show more articles