[HTML][HTML] Segmentation of the prostate, its zones, anterior fibromuscular stroma, and urethra on the MRIs and multimodality image fusion using U-Net model
SM Rezaeijo, SJ Nesheli, MF Serj… - Quantitative Imaging in …, 2022 - ncbi.nlm.nih.gov
Background Due to the large variability in the prostate gland of different patient groups,
manual segmentation is time-consuming and subject to inter-and intra-reader variations.
Hence, we propose a U-Net model to automatically segment the prostate and its zones,
including the peripheral zone (PZ), transitional zone (TZ), anterior fibromuscular stroma
(AFMS), and urethra on the MRI [T2-weighted (T2W), diffusion-weighted imaging (DWI), and
apparent diffusion coefficient (ADC)], and multimodality image fusion. Methods A total of 91 …
manual segmentation is time-consuming and subject to inter-and intra-reader variations.
Hence, we propose a U-Net model to automatically segment the prostate and its zones,
including the peripheral zone (PZ), transitional zone (TZ), anterior fibromuscular stroma
(AFMS), and urethra on the MRI [T2-weighted (T2W), diffusion-weighted imaging (DWI), and
apparent diffusion coefficient (ADC)], and multimodality image fusion. Methods A total of 91 …
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