Machine learning in prostate MRI for prostate cancer: current status and future opportunities

H Li, CH Lee, D Chia, Z Lin, W Huang, CH Tan - Diagnostics, 2022 - mdpi.com
Advances in our understanding of the role of magnetic resonance imaging (MRI) for the
detection of prostate cancer have enabled its integration into clinical routines in the past two …

Deep learning prostate MRI segmentation accuracy and robustness: a systematic review

MK Fassia, A Balasubramanian, S Woo… - Radiology: Artificial …, 2024 - pubs.rsna.org
Purpose To investigate the accuracy and robustness of prostate segmentation using deep
learning across various training data sizes, MRI vendors, prostate zones, and testing …

nnDetection: a self-configuring method for medical object detection

M Baumgartner, PF Jäger, F Isensee… - … Image Computing and …, 2021 - Springer
Simultaneous localisation and categorization of objects in medical images, also referred to
as medical object detection, is of high clinical relevance because diagnostic decisions often …

Customized efficient neural network for COVID-19 infected region identification in CT images

A Stefano, A Comelli - Journal of Imaging, 2021 - mdpi.com
Background: In the field of biomedical imaging, radiomics is a promising approach that aims
to provide quantitative features from images. It is highly dependent on accurate identification …

CAT-Net: A cross-slice attention transformer model for prostate zonal segmentation in MRI

ALY Hung, H Zheng, Q Miao, SS Raman… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Prostate cancer is the second leading cause of cancer death among men in the United
States. The diagnosis of prostate MRI often relies on accurate prostate zonal segmentation …

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 …

A New Preclinical Decision Support System Based on PET Radiomics: A Preliminary Study on the Evaluation of an Innovative 64Cu-Labeled Chelator in Mouse …

V Benfante, A Stefano, A Comelli, P Giaccone… - Journal of …, 2022 - mdpi.com
The 64Cu-labeled chelator was analyzed in vivo by positron emission tomography (PET)
imaging to evaluate its biodistribution in a murine model at different acquisition times. For …

Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network

Y Kurata, M Nishio, Y Moribata, A Kido, Y Himoto… - Scientific Reports, 2021 - nature.com
Endometrial cancer (EC) is the most common gynecological tumor in developed countries,
and preoperative risk stratification is essential for personalized medicine. There have been …

Region-adaptive magnetic resonance image enhancement for improving CNN-based segmentation of the prostate and prostatic zones

DI Zaridis, E Mylona, N Tachos, VC Pezoulas… - Scientific Reports, 2023 - nature.com
Automatic segmentation of the prostate of and the prostatic zones on MRI remains one of the
most compelling research areas. While different image enhancement techniques are …

A multi-scale channel attention network for prostate segmentation

M Ding, Z Lin, CH Lee, CH Tan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Prostate cancer is one of the most common malignant tumors in men. Magnetic resonance
imaging (MRI) has evolved to an important tool for the diagnosis of prostate cancer …