Register for updates

 
 

Computers & Technology
RSS Feed
TAU Uses “Deep Learning” to Assist Overburdened Diagnosticians
Monday, April 04, 2016 9:21:00 AM

Researcher engineers a cutting-edge solution for radiologists and other medical staff

Some 2 billion X-rays are performed around the world every year. But the average radiology clinic is understaffed. Radiologists are burdened with a growing workload, allowing little time to comprehensively evaluate images — leading to misdiagnoses and more serious consequences.

Now a Tel Aviv University lab is engineering practical solutions to meet the demands of radiologists. Prof. Hayit Greenspan's Medical Image Processing Lab in the Department of Biomedical Engineering in the TAU Faculty of Engineering has developed a wide variety of tools to facilitate computer-assisted diagnosis of X-rays, CTs and MRIs, freeing radiologists to attend to complex cases that require their full attention and skills.

"There is a shortage of radiologists, and their workload continues to grow. This means that some X-rays are never read or are only read following a long, life-endangering delay," said Prof. Greenspan. "Our goal is to use computer-assisted 'Deep Learning' technologies to differentiate between healthy and non-healthy patients, and to categorize all pathologies present in a single image through an efficient and robust framework that can be adapted to a real clinical setting."

"Deep learning" for accurate diagnosis

Prof. Greenspan discussed her lab's plan to implement "Deep Learning," a new area of Machine Learning research that harnesses artificial intelligence for various scientific fields, at the Israeli Symposium on Computational Radiology held at TAU last December. Her goal is to use Deep Learning to develop diagnostic tools for the automated detection and labelling of pathologies in radiographic images.

Prof. Greenspan's lab is one of only a few labs in the world dedicated to the application of Deep Learning in medicine. She and her team have already developed the technology to support automated chest X-ray pathology identification using Deep Learning, liver lesion detection, MRI lesion analysis and other tasks.

"We have developed tools to support decision-making in radiology with computer vision and machine learning algorithms. This will help radiologists make more accurate, more quantitative and more objective decisions," said Prof. Greenspan. "This is especially crucial when it comes to initial screenings. Such systems can improve accuracy and efficiency in both basic and more advanced radiology departments around the world."

Prof. Greenspan is also exploring the use of "transfer learning" in her research on the medical applications of Deep Learning. "Crowdsourcing was essential for the application of Deep Learning on general image searches such as Google search," said Prof. Greenspan. "But when it comes to medical imaging, there are privacy issues and there’s very little comprehensive data available at this point.

"In 'transfer learning,' we use networks originally trained on regular images to categorize medical images. The features and parameters that represent millions of general images provide a good signature for the analysis of medical images as well."

Prof. Greenspan's work is supported by the INTEL Collaborative Research Institute for Computational Intelligence (ICRI-CI) and the Israeli Finance Ministry, in collaboration with Sheba Medical Center. She is also head co-editor of a special issue on "Deep Learning in Medical Imaging," which will be published in the journal IEEE Transactions on Medical Imaging in May.




Latest News

Study Finds Prehistoric Humans Ate Bone Marrow Like Canned Soup 400,000 Years Ago

Bone and skin preserved the nutritious marrow for later consumption, TAU researchers say.

TAU and Ichilov Researchers Develop Innovative Treatment for Familial Adenomatous Polyposis

Adolescents and young adults with the inherited disorder bear a high risk of developing colorectal cancer.

Engineered T Cells May Be Harnessed to Kill Solid Tumor Cells

Novel immunotherapy extends therapy now used in fighting leukemia, TAU researchers say.

Researchers Discover How a Protein Connecting Calcium and Plant Hormone Regulates Plant Growth

Mechanism enables plants to adapt their development to their environment, TAU researchers say.

LocalTAU Top Scientists Move Closer to Securing Pilot Program in Miami

Fellows from competition return to Miami to present at marine health summit and participate in high-level meetings.

TAU Researchers Discover Evidence of Biblical Kingdom of Edom in Arava Desert

Findings also suggest pharaoh's influence on Edom turned kingdom into copper powerhouse, say TAU researchers.

Business and Civic Leader Mort Mandel Awarded TAU Honorary Doctorate

Mr. Mandel cited for his visionary philanthropy and establishment of the Jack, Joseph and Morton Mandel Center for STEM and the Humanities at TAU.

Early Humans Used Tiny, Flint "Surgical" Tools to Butcher Elephants

New discovery by TAU-led research group suggests early humans in the Levant were sophisticated and environmentally conscious.

TAU Ranks Among Top 10 Undergraduate Programs Producing Most Venture Capital-Backed Entrepreneurs

Joining Stanford, UC Berkeley, and MIT, TAU is the only non-U.S. university to make top 10 of global VC list.

Protein Mapping Pinpoints Why Most Metastatic Melanoma Patients Do Not Respond to Immunotherapy

Lipid metabolism found to affect cancer cells' visibility to the immune system, say TAU, Sheba Medical Center researchers.

contentSecondary
c

© 2019 American Friends of Tel Aviv University
39 Broadway, Suite 1510 | New York, NY 10006 | 212.742.9070 | info@aftau.org
Privacy policy | Tel Aviv University