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Image: Comparison of two example mammograms from DDSM and INbreast (Photo courtesy of ResearchGate).

Deep Learning-Based System Detects and Classifies Mammogram Masses

Researchers from the Kyung Hee University have developed a fully integrated computer-aided diagnosis (CAD) system that uses deep learning and a deep convolutional neural network (CNN) to detect, segment and classify masses from mammograms. In a new study published by the International Journal of Medical Informatics, the researchers have described the use of their regional deep learning model, You-Only-Look-Once (YOLO), to detect breast mass from entire mammograms. The researchers then went on to use a new deep network model based on a full resolution convolutional network (FrCN), to segment the mass lesions pixel-to-pixel. Finally, a deep CNN was used to recognize the mass and classify it as either benign or malignant. More...
16 Aug 2018
Image: MRI reconstruction example. (a) Input image with only 10% of spectrum samples retained and scaled by 1/p. (b) Reconstruction by a network trained with noisy target images similar to the input image. (c) Original, uncorrupted image (Photo courtesy of NVIDIA).

AI Software for Restoring Photos Could Find Use in Medical Imaging

Researchers have developed a deep learning-based approach that can fix photos originally taken in low light and are grainy or pixilated, and automatically remove the noise and artifacts by simply looking at examples of corrupted photos only. The approach can also be used to enhance MRI images, which could pave the way for a drastic improvement in medical imaging. More...
16 Aug 2018
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Image: A new report suggests that video conferencing between radiology and ICU professionals could enhance patient care (Photo courtesy of iStock).

Video Conference Could Facilitate Relationships between Radiologists and ICU Clinicians

Radiologists and intensive care unit (ICU) clinicians who have not been connected for a decade can improve their relationships as well as quality of care through immersive video conference, according to a group of physicians from the Children’s Hospital of Philadelphia. More...
16 Aug 2018
Image: The AI-based deep-learning solution is designed to assist workflow triage and improve response time (Photo courtesy of Aidoc).

FDA Gives Clearance to World's First Deep-Learning Solution to Assist Workflow Triage

A brain solution that works with radiologists to flag acute intracranial hemorrhage (ICH) cases in head CTs and is the world's first deep-learning solution to assist radiologists in workflow triage has been granted clearance by the Food and Drug Administration (FDA). The product is the first of the expanding suite of artificial intelligence (AI)-based workflow optimization solutions to be offered by Aidoc, a provider of AI solutions for radiologists. More...
15 Aug 2018
Image: Researchers have developed a deep learning–based system for cartilage lesion detection in knee MR images (Photo courtesy of Health Imaging).

Deep Learning-Based System Detects Lesions in Knee MR Images

Researchers from the department of radiology at the University of Wisconsin School of Medicine and Public Health have developed a deep learning approach to detect cartilage lesions by evaluating MR images of the knee. The researchers used segmentation and classification convolutional neural networks (CNNs) to develop the fully automated deep learning–based cartilage lesion detection system. More...
10 Aug 2018
Image: Aaron Babier shows the screen from the new AI software (Photo courtesy of Brian Tran).

New AI Software Cuts Radiation Therapy Planning Time

Researchers from the University of Toronto have developed automation software that will cut down the time for developing radiation therapy plans — individualized maps that help doctors determine where to blast tumors — from days to mere hours. More...
10 Aug 2018
Image: RSNA 2018 will focus on machine learning and the potential of AI in radiology (Photo courtesy of ShutterStock).

RSNA Announces AI and Machine-Learning Initiatives for 2018

The Radiological Society of North America has planned a diverse roster of machine learning (ML) and artificial intelligence (AI) programming for RSNA 2018 that will focus on the power and potential of AI in radiology and issues associated with implementation. More...
10 Aug 2018
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