Clean Sweep Live Auction on Thur. March 28th. Click to view the full inventory

DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Mobile Imaging
Current Location:
> This Story

Log in or Register to rate this News Story
Forward Printable StoryPrint Comment




Cardiology Homepage

Apple study suggests wearable technology may be useful in detecting atrial fibrillation May assist in stroke and hospitalization prevention

Echocardiogram should play role in patient selection for transcatheter mitral valve repair, says study New study highlighted at ACC

FDA gives green light for smallest, slimmest 3T CRM devices Extended battery lives, greater diagnostic and therapeutic capabilities

Level Ex releases interventional cardiac video game, Cardio Ex Over 35 levels that test cognitive, spatial reasoning and decision-making skills

Siemens to unveil its SOMATOM go.Top Cardiovascular Edition CT at ACC 19 Ideal for the cardiovascular outpatient setting

FDA approves Sonavex's EchoSure system Monitors blood flow following surgical procedures

Siemens unveils Artis icono biplane angio system at ECR Enables diagnostics and treatment to take place in same lab, improved 2D and 3D capabilities

Personalized cardiac test could eliminate unnecessary catheterizations Examines flow of blood with AI and CT

Noninvasive approach for imaging carotid artery shows promise Enables risk assessment for cardiovascular disease

Medtronic to acquire EPIX Therapeutics Will use EPIX's cardiac ablation technology with Medtronic's cryoballoon technology

The AI system can classify intracranial
hemorrhages from small data sets and
explain the reasoning behind its decision

New AI system classifies hemorrhages using small data sets

by John R. Fischer , Staff Reporter
Researchers at the Massachusetts General Hospital (MGH) Department of Radiology have developed an AI system capable of classifying different forms of intracranial hemorrhage using relatively small data sets.

A possible tool for assessing patients with symptoms of potentially life-threatening strokes, the system is capable of producing a quick diagnosis and explaining the reasoning behind it, offering confidence to facilities which may not have access to specially trained neuroradiologists, and addressing the so-called “black box” challenge, in which systems are unable to explain how they arrived at a decision.

Story Continues Below Advertisement

RaySafe helps you avoid unnecessary radiation

RaySafe solutions are designed to minimize the need for user interaction, bringing unprecedented simplicity & usability to the X-ray room. We're committed to establishing a radiation safety culture wherever technicians & medical staff encounter radiation.

“In medicine, it is especially hard to collect high-quality big data. It is critical to have multiple experts label a data set to ensure consistency of data. This process is very expensive and time-consuming. Some critics suggest that machine learning algorithms cannot be used in clinical practice, because the algorithms do not provide justification for their decisions. We realized that it is imperative to overcome these two challenges to facilitate the use in health care of machine learning, which has an immense potential to improve the quality of and access to care," authors Sehyo Yune, the director of researcher translation at MGH Radiology, and Hyunkwang Lee, a graduate student at the Harvard School of Engineering and Applied Sciences, said in a statement.

The FDA requires that all decision support systems provide data for users to review the reasoning behind their findings.

Trained on 904 head CT scans, the MGH solution classifies images into one of five hemorrhage subtypes, based on the location of the brain, or as no hemorrhage, reviewing and saving images from the training data set that most accurately represent the traditional features found in each classification. It then uses an atlas of distinguishing features to show a group of images similar to those of the CT scan under evaluation to explain its diagnosis.

The team designed the system to mimic the way in which radiologists analyze images, incorporating adjusting factors such as contrast and brightness for revealing subtle differences that are not immediately apparent, and the ability to scroll through adjacent CT scans to determine whether or not a finding on a single image reflects a real problem or is a meaningless artifact.

Following its completion, the researchers tested the system on a retrospective set of 100 scans with and 100 scans without intracranial hemorrhages that were taken before the system was developed, and on a prospective set that was taken after its creation of 79 scans with and 117 without hemorrhages.
  Pages: 1 - 2 >>

Cardiology Homepage

You Must Be Logged In To Post A Comment

Increase Your
Brand Awareness
Auctions + Private Sales
Get The
Best Price
Buy Equipment/Parts
Find The
Lowest Price
Daily News
Read The
Latest News
Browse All
DOTmed Users
Ethics on DOTmed
View Our
Ethics Program
Gold Parts Vendor Program
Receive PH
Gold Service Dealer Program
Receive RFP/PS
Healthcare Providers
See all
HCP Tools
A Job
Parts Hunter +EasyPay
Get Parts
Recently Certified
View Recently
Certified Users
Recently Rated
View Recently
Certified Users
Rental Central
Rent Equipment
For Less
Sell Equipment/Parts
Get The
Most Money
Service Technicians Forum
Find Help
And Advice
Simple RFP
Get Equipment
Virtual Trade Show
Find Service
For Equipment
Access and use of this site is subject to the terms and conditions of our LEGAL NOTICE & PRIVACY NOTICE
Property of and Proprietary to DOTmed.com, Inc. Copyright ©2001-2019 DOTmed.com, Inc.