The following Content Areas will be printed on the certificate for this course:
- Informatics
Course Learning Objectives:
- Discuss the key concepts underlying deep learning with CNNs.
- Describe emerging applications of deep learning techniques to radiology for lesion classification, detection, and segmentation.
- List key technical requirements in terms of dataset, hardware, and software required to perform deep learning.
This journal-based CME activity is estimated to take 1 hour to complete.
Online Course Start Date: 11/13/2017
End Date for CME Eligibility/Online Expiration Date: 11/12/2020
Authors:
- Gabriel Chartrand, PhD
- Phillip M. Cheng, MD, MS
- Eugene Vorontsov, BASc Eng Sci
- Michal Drozdzal, PhD
- Simon Turcotte, MD, MSc
- Christopher J. Pal, PhD
- Samuel Kadoury, PhD
- An Tang, MD, MSc
Disclosure Statements:
The ACCME requires that the RSNA, as an accredited provider of CME, disclose the relevant financial relationships of the planners, faculty, and any other individuals in a position to control content of this activity. If there is a relevant financial relationship that has been disclosed please find it below:
- G.C.: Activities related to the present article: grant from Imagia Cybernetics. Activities not related to the present article: disclosed no relevant relationships. Other activities: disclosed no relevant relationships.
- E.V.: Activities related to the present article: grant from Imagia Cybernetics. Activities not related to the present article: disclosed no relevant relationships. Other activities: disclosed no relevant relationships.
- C.J.P.: Activities related to the present article: grant from Imagia Cybernetics. Activities not related to the present article: disclosed no relevant relationships. Other activities: disclosed no relevant relationships.
- A.T.: Activities related to the present article: grant from Imagia Cybernetics. Activities not related to the present article: disclosed no relevant relationships. Other activities: disclosed no relevant relationships.
All other individuals in control of content have indicated that they have no relevant financial relationships to disclose for this activity.
Accreditation and Designation Statements:
The Radiological Society of North America (RSNA) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
This journal-based CME activity can be applied towards the ABR MOC self-assessment requirement (SA-CME).
To earn CME credit, participants must correctly answer a minimum of 80% of the post-test questions and complete the course evaluation.
The RSNA designates this journal-based CME activity for a maximum of 1.00 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
This journal-based CME activity is an Accredited Self-Assessment Program (Section 3) as defined by the NEW Maintenance of Certification program (MOC) of the Royal College of Physicians and Surgeons of Canada (RCPSC), and has been approved by the Canadian Association of Radiologists (CAR) for a maximum of 1 credit hours per activity. The RCPSC recording system (MAINPORT) will automatically convert the credit hours for this program to three credits per claimed hour (1 hours x 3 = 3 credit hours). Physicians should only claim credits commensurate with the extent of their participation in the activity. Accreditation services do not imply endorsement of opinions presented during the activity.
Price:
Non-member Rate: $35.00
Member Rate: $0.00
Refund / Exchange Policy:
RSNA will not issue any refunds or exchanges for online only versions of educational products or activities purchased online. Please review the entire product or activity description prior to purchase.
RSNA Disclaimer:
The opinions or views expressed in this activity are those of the presenters and do not necessarily reflect the opinions, recommendations or endorsement of the RSNA. Participants should critically appraise the information presented and are encouraged to consult appropriate resources for information surrounding any product or device mentioned. Information presented, as well as publications, technologies, products and/or services discussed, are intended to inform the learner about the knowledge, techniques, and experiences of RSNA faculty who are willing to share such information with colleagues. The RSNA disclaims any and all liability for damages to any individual user for all claims which may result from the use of said information, publications, technologies, products and/or services, and events.