Fully automated detection of prostate transition zone tumors on T2‐weighted and apparent diffusion coefficient (ADC) map MR images using U‐Net ensemble-Reference-Cited by-同舟云学术

Fully automated detection of prostate transition zone tumors on T2‐weighted and apparent diffusion coefficient (ADC) map MR images using U‐Net ensemble

Published:2021-08-30 Issue:11 Volume:48 Page:6889-6900
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Wong Timothy¹,Schieda Nicola²,Sathiadoss Paul²,Haroon Mohammad²,Abreu‐Gomez Jorge³,Ukwatta Eranga¹

Affiliation:

1. School of Engineering University of Guelph Guelph ON Canada

2. Department of Radiology University of Ottawa Ottawa ON Canada

3. Joint Department of Medical Imaging University of Toronto Toronto ON Canada

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15181

Reference56 articles.

1. Support Vector Machines (SVM) classification of prostate cancer Gleason score in central gland using multiparametric magnetic resonance images: A cross-validated study

2. Meta-Analysis of Prostate-Specific Antigen and Digital Rectal Examination as Screening Tests for Prostate Carcinoma

3. Diagnostic Value of Systematic Biopsy Methods in the Investigation of Prostate Cancer: A Systematic Review

4. The Diagnosis and Treatment of Prostate Cancer

5. INCIDENCE AND CLINICAL SIGNIFICANCE OF FALSE-NEGATIVE SEXTANT PROSTATE BIOPSIES

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