Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI-Reference-Cited by-同舟云学术

Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI

Published:2024-07 Issue:7 Volume:43 Page:2610-2622
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Rajagopal Abhejit¹^ORCID,Westphalen Antonio C.²,Velarde Nathan¹,Simko Jeffry P.³,Nguyen Hao⁴,Hope Thomas A.¹^ORCID,Larson Peder E. Z.¹^ORCID,Magudia Kirti⁵^ORCID

Affiliation:

1. Department of Radiology and Biomedical Imaging, University of California at San Francisco, San Francisco, CA, USA

2. Department of Radiology, University of Washington, Seattle, WA, USA

3. Department of Pathology, University of California at San Francisco, San Francisco, CA, USA

4. Department of Urology, University of California at San Francisco, San Francisco, CA, USA

5. Department of Radiology, Duke University, Durham, NC, USA

Funder

National Institute of Health, National Institute of Biomedical Imaging and Bioengineering

NIH/National Cancer Institute

University of California, San Francisco (UCSF) Benioff Initiative for Prostate Cancer Research, a Society for Abdominal Radiology Morton A. Bosniak Research Award

RSNA Research Fellow Grant

Cancer League

Helen Diller Family Comprehensive Cancer Center, UCSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/42/10579886/10483083.pdf?arnumber=10483083

Reference27 articles.

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2. Prostate cancer detection with magnetic resonance-ultrasound fusion biopsy: The role of systematic and targeted biopsies

3. Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel

4. The Low Rate of Adherence to Checklist for Artificial Intelligence in Medical Imaging Criteria Among Published Prostate MRI Artificial Intelligence Algorithms