Deep learning prostate MRI segmentation accuracy and robustness: a systematic review
Purpose To investigate the accuracy and robustness of prostate segmentation using deep
learning across various training data sizes, MRI vendors, prostate zones, and testing …
learning across various training data sizes, MRI vendors, prostate zones, and testing …
[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …
respect to the quantity of high-performing solutions reported in the literature. End users are …
Learning calibrated medical image segmentation via multi-rater agreement modeling
In medical image analysis, it is typical to collect multiple annotations, each from a different
clinical expert or rater, in the expectation that possible diagnostic errors could be mitigated …
clinical expert or rater, in the expectation that possible diagnostic errors could be mitigated …
[HTML][HTML] Test-time adaptable neural networks for robust medical image segmentation
Abstract Convolutional Neural Networks (CNNs) work very well for supervised learning
problems when the training dataset is representative of the variations expected to be …
problems when the training dataset is representative of the variations expected to be …
[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 …
manual segmentation is time-consuming and subject to inter-and intra-reader variations …
Automatic segmentation with deep learning in radiotherapy
Simple Summary Automatic segmentation of organs and other regions of interest is a
promising approach for reducing the workload of doctors in radiotherapeutic planning, but it …
promising approach for reducing the workload of doctors in radiotherapeutic planning, but it …
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 …
U-Net architecture for prostate segmentation: the impact of loss function on system performance
Segmentation of the prostate gland from magnetic resonance images is rapidly becoming a
standard of care in prostate cancer radiotherapy treatment planning. Automating this …
standard of care in prostate cancer radiotherapy treatment planning. Automating this …
Magnetic resonance imaging based radiomic models of prostate cancer: A narrative review
Simple Summary The increasing interest in implementing artificial intelligence in radiomic
models has occurred alongside advancement in the tools used for computer-aided …
models has occurred alongside advancement in the tools used for computer-aided …
The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics
M Kaneko, V Magoulianitis, LS Ramacciotti… - Urologic …, 2024 - urologic.theclinics.com
The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging - Urologic Clinics
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