2024
DOI: 10.21037/qims-23-1698
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3D EAGAN: 3D edge-aware attention generative adversarial network for prostate segmentation in transrectal ultrasound images

Mengqing Liu,
Xiao Shao,
Liping Jiang
et al.

Abstract: Background The segmentation of prostates from transrectal ultrasound (TRUS) images is a critical step in the diagnosis and treatment of prostate cancer. Nevertheless, the manual segmentation performed by physicians is a time-consuming and laborious task. To address this challenge, there is a pressing need to develop computerized algorithms capable of autonomously segmenting prostates from TRUS images, which sets a direction and form for future development. However, automatic prostate segmentation … Show more

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