BioAug-Net: a bioimage sensor-driven attention-augmented segmentation framework with physiological coupling for early prostate cancer detection in T2-weighted MRI

BioAug-Net: a bioimage sensor-driven attention-augmented segmentation framework with physiological coupling for early prostate cancer detection in T2-weighted MRI

Abstract Accurate segmentation of the prostate peripheral zone (PZ) in T2-weighted MRI is critical for the early detection of prostate cancer. Existing segmentation methods are hindered by significant inter-observer variability (37.4 ± 5.6%), poor boundary localization, and the presence of motion ar...

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Bibliographic Details
Main Authors: Muhammad Arshad, Chengliang Wang, Muhammad Wajeeh Us Sima, Jamshed Ali Shaikh, Hanen Karamti, Raed Alharthi, Julius Selecky
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BioData Mining
Subjects:
Prostate cancer
Bioimage processing
T2-weighted MRI
Image segmentation
Attention mechanism
Clinical decision support system
Online Access:https://doi.org/10.1186/s13040-025-00467-4
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https://doi.org/10.1186/s13040-025-00467-4

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