[HTML][HTML] Automatic segmentation of prostate zonal anatomy on MRI: a systematic review of the literature
C Wu, S Montagne, D Hamzaoui, N Ayache… - Insights into …, 2022 - Springer
Objectives Accurate zonal segmentation of prostate boundaries on MRI is a critical
prerequisite for automated prostate cancer detection based on PI-RADS. Many articles have …
prerequisite for automated prostate cancer detection based on PI-RADS. Many articles have …
National cancer institute imaging data commons: toward transparency, reproducibility, and scalability in imaging artificial intelligence
The remarkable advances of artificial intelligence (AI) technology are revolutionizing
established approaches to the acquisition, interpretation, and analysis of biomedical …
established approaches to the acquisition, interpretation, and analysis of biomedical …
Exploring uncertainty measures in Bayesian deep attentive neural networks for prostate zonal segmentation
Automatic segmentation of prostatic zones on multi-parametric MRI (mpMRI) can improve
the diagnostic workflow of prostate cancer. We designed a spatial attentive Bayesian deep …
the diagnostic workflow of prostate cancer. We designed a spatial attentive Bayesian deep …
Automatic prostate zonal segmentation using fully convolutional network with feature pyramid attention
Our main objective in the paper is to develop a novel deep learning-based algorithm for
automatic segmentation of prostate zones and to evaluate the performance of the algorithm …
automatic segmentation of prostate zones and to evaluate the performance of the algorithm …
Graph‐convolutional‐network‐based interactive prostate segmentation in MR images
Purpose Accurate and robust segmentation of the prostate from magnetic resonance (MR)
images is extensively applied in many clinical applications in prostate cancer diagnosis and …
images is extensively applied in many clinical applications in prostate cancer diagnosis and …
CCT-Unet: A U-shaped Network based on Convolution Coupled Transformer for Segmentation of Peripheral and Transition Zones in Prostate MRI
Y Yan, R Liu, H Chen, L Zhang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
The accurate segmentation of prostate region in magnetic resonance imaging (MRI) can
provide reliable basis for artificially intelligent diagnosis of prostate cancer. Transformer …
provide reliable basis for artificially intelligent diagnosis of prostate cancer. Transformer …
Anisotropic 3D multi-stream CNN for accurate prostate segmentation from multi-planar MRI
Abstract Background and Objective: Accurate and reliable segmentation of the prostate
gland in MR images can support the clinical assessment of prostate cancer, as well as the …
gland in MR images can support the clinical assessment of prostate cancer, as well as the …
[HTML][HTML] Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology
S Montagne, D Hamzaoui, A Allera, M Ezziane… - Insights into …, 2021 - Springer
Background Accurate prostate zonal segmentation on magnetic resonance images (MRI) is
a critical prerequisite for automated prostate cancer detection. We aimed to assess the …
a critical prerequisite for automated prostate cancer detection. We aimed to assess the …
Deep learning in magnetic resonance prostate segmentation: A review and a new perspective
D Gillespie, C Kendrick, I Boon, C Boon… - arXiv preprint arXiv …, 2020 - arxiv.org
Prostate radiotherapy is a well established curative oncology modality, which in future will
use Magnetic Resonance Imaging (MRI)-based radiotherapy for daily adaptive radiotherapy …
use Magnetic Resonance Imaging (MRI)-based radiotherapy for daily adaptive radiotherapy …
Training auxiliary prototypical classifiers for explainable anomaly detection in medical image segmentation
Abstract Machine learning-based algorithms using fully convolutional networks (FCNs) have
been a promising option for medical image segmentation. However, such deep networks …
been a promising option for medical image segmentation. However, such deep networks …