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.
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.
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…
Artificial Intelligence is an essential tool for the healthcare operators on the front line in the fight against the Coronavirus pandemic. ASST Vimercate Hospital chose and implemented in the midst of the COVID-19 emergency REiLI, Fujifilm Medical Systems’ Artificial Intelligence.
In a collaboration between Google Brain, Intel Corporation and the University of California, Berkeley, researchers have 'trained' robots to mimic surgical procedures through the use of instructional videos.
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.
An algorithm that analyses MRI images and automatically detects small changes in knee joints over time could be used in the development of new treatments for arthritis. A team of engineers, radiologists and physicians, led by the University of Cambridge, developed the algorithm, which builds a three-dimensional model of an individual’s knee joint in order to map where arthritis is affecting the…
A new machine learning approach classifies a common type of brain tumour into low or high grades with almost 98% accuracy, researchers report in the journal IEEE Access. Scientists in India and Japan, including from Kyoto University’s Institute for Integrated Cell-Material Sciences (iCeMS), developed the method to help clinicians choose the most effective treatment strategy for individual…
Computer scientists working with pathologists have trained an artificial intelligence (AI) tool to determine which patients with lung cancer have a higher risk of their disease coming back after treatment. The AI tool was able to differentiate between immune cells and cancer cells, enabling researchers to build a detailed picture of how lung cancers evolve in response to the immune system in…
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,…
Establishing whether a patient is suffering from severe lung disease, possibly COVID-19, within a few minutes: this is possible using fairly simple ultrasound machines that are enhanced with artificial intelligence. A research team at Eindhoven University of Technology (TU/e) and the University of Trento in Italy has been able to translate the expertise of top lung specialists into a software…
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…
Computed tomography (CT) is one of the most effective medical tests for analysing the effects of many illnesses, including COVID-19, on the lungs. An international team led by the Universitat Oberta de Catalunya (UOC) has developed a new method that improves the quality of the images obtained from CT scans. The algorithm, which has been tested on simulated data, enables them to distinguish…
Researchers at King’s College London, Massachusetts General Hospital and health science company ZOE have developed an artificial intelligence (AI) diagnostic that can predict whether someone is likely to have COVID-19 based on their symptoms. Their findings are published in Nature Medicine. The AI model uses data from the COVID Symptom Study app to predict COVID-19 infection, by comparing…
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).
Researchers at Northwestern University are using artificial intelligence (AI) to speed up the search for COVID-19 treatments and vaccines. The AI-powered tool makes it possible to prioritize resources for the most promising studies — and ignore research that is unlikely to yield benefits. In the midst of the pandemic, scientific research is being conducted at an unprecedented rate. The Food and…