AAPM VL-Deep Learning and Applications in Medical Imaging

2017 AAPM Annual Meeting - Session: Deep Learning and Applications in Medical Imaging

Deep Learning: Principles, Achievements and Future Potential in Medical Imaging
Berkman Sahiner, PhD US Food and Drug Administration
berkman.sahiner@fda.hhs.gov

Handout(s):

127-35326-418554-126897.pdf

When you have finished the video, you may watch again, browse/search all videos, go back to the previous page, or watch another video in this session (see below). add this video to a playlist.

There is a quiz associated with this video in our Online Continuing Education Center. Please click here to try the quiz.

All videos in this session:

	Can Deep Learning Help in Cancer Diagnosis and Treatment? - Lubomir Hadjiiski, PhD University of Michigan
	Role of Deep Learning at Various Stages of Quantitative Image Analysis for Disease Assessment - Maryellen Giger, PhD University Chicago
	The Impact of Deep Learning On Radiology - Ronald Summers, PhD NIH Clinical Center
	Q & A -

Graph includes 512 member loads and 4327 non-member loads (4839 total loads). Exclude non-member? A load is defined as someone coming to this page, not necesarily that they pressed play, or watched the entire presentation.

AAPM is the American Association of Physicists in Medicine.
1631 Prince Street
Alexandria, VA 22314
Phone 571-298-1300
Fax 571-298-1301 
Send general questions to 2022.aapm@aapm.org

AAPM's Privacy Policy
Use of the site constitutes your acceptance to its terms and conditions.

AAPM is a scientific, educational, and professional nonprofit organization devoted to the discipline of physics in medicine. The information provided in this website is offered for the benefit of its members and the general public, however, AAPM does not independently verify or substantiate the information provided on other websites that may be linked to this site.

AAPM Virtual Library

2017 AAPM Annual Meeting - Session: Deep Learning and Applications in Medical Imaging