Currently, ultrasound machines are operated primarily by specialists because it requires extensive experience to interpret the images. Norwegian researchers are aiming to tackle this issue.
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’.…
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…
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…
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…
Artificial Intelligence (AI) has, for the first time, measured blood flow to the heart to help predict which patients may suffer myocardial infarction or stroke. A research team at University College London and Barts Health NHS Trust and the National Institutes for Health (NIH) in the USA – are optimistic that AI analysis of perfusion maps will be a reliable, convenient and detailed new…
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.
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…
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…
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…
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…
40 years ago, anticipating the huge impact of computers in radiology, a group of visionaries formed the Radiology Information System Consortium (RISC). In 1989, RISC created the Society for Computer Applications (SCAR) to promote computer applications in digital imaging. Those organisations became the Society for Imaging Informatics in Medicine (SIIM). At SIIM 2020, a virtual meeting, experts…
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…
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…
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…
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…
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…
Dr Francis Zarb, senior radiography lecturer at the University of Malta, outlined challenges in correctly positioning patients needing musculoskeletal imaging. During our interview, he also offered a brief insight into the use of artificial intelligence (AI) in radiography today.
The Artificial Intelligence (AI) landscape confronting the radiographer profession will be outlined in sessions at ECR 2020, with leading practitioners urging the need for an evidence-based approach in order to deliver a safe and effective service for patients. The session, under the broad heading of “Artificial intelligence and the radiographer profession”, aims to discuss AI within the…
The AI-Rad Companion family supports radiologists, radiation oncologists, radiotherapists and medical physicists through automated post processing of MRI, CT and X-ray datasets. It saves the clinicians' time and helps them to increase their diagnostic precision.
The complex form of machine learning DLIR (Deep Learning Image Reconstruction) is based on a deep neuronal network which is similar to the human brain. The artificial neurons of this network learn according to their biological model through intensive training. For the DLIR image reconstruction, the network is fed with sample data from phantom images on the one hand and high-resolution images of…
Thales’ expert knowledge in digital technology as well as in hardware and software systems has enabled the company to become a market leader in major innovation fields such as the cloud, connectivity and artificial intelligence. Thales is proud to launch its unique Connected Radiology platform which will bring multiple benefits to the efficiency of hospitals through the non-stop use of…
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.
