Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magnetic resonance imaging

Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magnetic resonance imaging

Abstract Automated prostate cancer detection in magnetic resonance imaging (MRI) scans is of significant importance for cancer patient management. Most existing computer‐aided diagnosis systems adopt segmentation methods while object detection approaches recently show promising results. The authors...

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Bibliographic Details
Main Authors: Zhe Min, Fernando J. Bianco, Qianye Yang, Wen Yan, Ziyi Shen, David Cohen, Rachael Rodell, Dean C. Barratt, Yipeng Hu
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
computer aided diagnosis
deep learning
magnetic resonance imaging (MRI)
medical image segmentation
medical object detection
prostate cancer detection
Online Access:https://doi.org/10.1049/cit2.12318
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