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A review of artificial intelligence in prostate cancer detection on imaging
A multitude of studies have explored the role of artificial intelligence (AI) in providing
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …
diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection …
[HTML][HTML] Advancements in mri-based radiomics and artificial intelligence for prostate cancer: A comprehensive review and future prospects
Simple Summary The integration of artificial intelligence (AI) into radiomic models has
become increasingly popular due to advances in computer-aided diagnosis tools. These …
become increasingly popular due to advances in computer-aided diagnosis tools. These …
Application of swarm intelligence optimization algorithms in image processing: A comprehensive review of analysis, synthesis, and optimization
M Xu, L Cao, D Lu, Z Hu, Y Yue - Biomimetics, 2023 - mdpi.com
Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …
intelligence. With the rise and development of machine learning and deep learning …
[HTML][HTML] A flexible 2.5 D medical image segmentation approach with in-slice and cross-slice attention
Deep learning has become the de facto method for medical image segmentation, with 3D
segmentation models excelling in capturing complex 3D structures and 2D models offering …
segmentation models excelling in capturing complex 3D structures and 2D models offering …
Fully automated deep learning model to detect clinically significant prostate cancer at MRI
Background Multiparametric MRI can help identify clinically significant prostate cancer
(csPCa)(Gleason score≥ 7) but is limited by reader experience and interobserver variability …
(csPCa)(Gleason score≥ 7) but is limited by reader experience and interobserver variability …
Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts?–a …
Purpose The purpose of this study was to perform a systematic review of the literature on the
diagnostic performance, in independent test cohorts, of artificial intelligence (AI)-based …
diagnostic performance, in independent test cohorts, of artificial intelligence (AI)-based …
RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate
Image registration can map the ground truth extent of prostate cancer from histopathology
images onto MRI, facilitating the development of machine learning methods for early …
images onto MRI, facilitating the development of machine learning methods for early …
Anatomically guided self-adapting deep neural network for clinically significant prostate cancer detection on bi-parametric MRI: a multi-center study
Objective To evaluate the effectiveness of a self-adapting deep network, trained on large-
scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in …
scale bi-parametric MRI data, in detecting clinically significant prostate cancer (csPCa) in …
[HTML][HTML] Magnetic resonance imaging-based predictive models for clinically significant prostate cancer: a systematic review
M Triquell, M Campistol, A Celma, L Regis, M Cuadras… - Cancers, 2022 - mdpi.com
Simple Summary Magnetic resonance imaging (MRI) has allowed the early detection of PCa
to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate …
to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate …
ProstAtlasDiff: Prostate cancer detection on MRI using Diffusion Probabilistic Models guided by population spatial cancer atlases
Abstract Magnetic Resonance Imaging (MRI) is increasingly being used to detect prostate
cancer, yet its interpretation can be challenging due to subtle differences between benign …
cancer, yet its interpretation can be challenging due to subtle differences between benign …