Prostate Age Gap

Prostate age gap (PAG) research aims to develop a more accurate and efficient method for prostate cancer risk assessment using magnetic resonance imaging (MRI). Current research focuses on leveraging deep learning models, including convolutional neural networks (CNNs) and transformer architectures, to automatically segment the prostate into zones and predict a patient's "prostate age" based on MRI characteristics, comparing it to their chronological age. This approach shows promise in improving the prediction of clinically significant prostate cancer, potentially leading to more personalized and effective diagnostic strategies. The improved accuracy and efficiency offered by PAG could significantly impact prostate cancer detection and treatment planning.

Papers

November 4, 2024

Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains
Robin Trombetta (MYRIAD), Olivier Rouvière (HCL), Carole Lartizien (MYRIAD)
Deep Learning Deep Learning Model Deep Model Tumor Segmentation Unseen Domain Medical Image Segmentation Task Cancer Detection Multi Parametric MRI Prostate Age Gap

July 9, 2024

AI-based Automatic Segmentation of Prostate on Multi-modality Images: A Review
Rui Jin, Derun Li, Dehui Xiang, Lei Zhang, Hailing Zhou, Fei Shi, Weifang Zhu, Jing Cai, Tao Peng, Xinjian Chen
Narrative Review Image Segmentation Learning Based Prostate Segmentation Multi Modality Image Prostate Age Gap

September 22, 2023

PI-RADS v2 Compliant Automated Segmentation of Prostate Zones Using co-training Motivated Multi-task Dual-Path CNN
Arnab Das, Suhita Ghosh, Sebastian Stober
Segmentation Accuracy Magnetic Resonance Image Dual Path Prostate Age Gap PI Rad

August 10, 2023

Prostate Age Gap (PAG): An MRI surrogate marker of aging for prostate cancer detection
Alvaro Fernandez-Quilez, Tobias Nordström, Fredrik Jäderling, Svein Reidar Kjosavik, Martin Eklund
Magnetic Resonance Imaging Prostate Cancer Gleason Grade Prostate Age Gap Surrogate Marker Prostate Cancer Whole Slide Image

May 31, 2023

Image Registration of In Vivo Micro-Ultrasound and Ex Vivo Pseudo-Whole Mount Histopathology Images of the Prostate: A Proof-of-Concept Study
Muhammad Imran, Brianna Nguyen, Jake Pensa, Sara M. Falzarano, Anthony E. Sisk, Muxuan Liang, John Michael DiBianco, Li-Ming Su, Yuyin Zhou, Wayne G. Brisbane, Wei Shao
Image Registration Ex Vivo Vivo Imaging Whole Slide Prostate Age Gap Micro Ultrasound

February 20, 2023

Non-rigid Medical Image Registration using Physics-informed Neural Networks
Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed, Mark Emberton, Dean C. Barratt, Zeike A. Taylor, Yipeng Hu
Physic Informed Neural Network Medical Image Registration Biomechanical Model Prostate Age Gap Ultrasound Registration

August 29, 2022

Comprehensive study of good model training for prostate segmentation in volumetric MRI
Carlos Nácher Collado
Convolutional Neural Network Model Training Comprehensive Study Prostate Cancer Prostate Segmentation Manual Segmentation Prostate Age Gap

August 24, 2022

Prostate Lesion Detection and Salient Feature Assessment Using Zone-Based Classifiers
Haoli Yin, Nithin Buduma
Magnetic Resonance Imaging Prostate Cancer Machine Learning Classifier Salient Feature Classification Rule Prostate Biopsy Prostate Age Gap

July 19, 2022

Comparison of automatic prostate zones segmentation models in MRI images using U-net-like architectures
Pablo Cesar Quihui-Rubio, Gilberto Ochoa-Ruiz, Miguel Gonzalez-Mendoza, Gerardo Rodriguez-Hernandez, Christian Mata
Consistent Comparison Image Segmentation Prostate Cancer Magnetic Resonance Image Architecture Perspective Prostate Segmentation Prostate Age Gap

March 29, 2022

CAT-Net: A Cross-Slice Attention Transformer Model for Prostate Zonal Segmentation in MRI
Alex Ling Yu Hung, Haoxin Zheng, Qi Miao, Steven S. Raman, Demetri Terzopoulos, Kyunghyun Sung
Magnetic Resonance Imaging Prostate Segmentation Inter Slice Prostate Age Gap Cross Slice Attention

Prostate Age Gap

Papers

Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains

AI-based Automatic Segmentation of Prostate on Multi-modality Images: A Review

PI-RADS v2 Compliant Automated Segmentation of Prostate Zones Using co-training Motivated Multi-task Dual-Path CNN

Prostate Age Gap (PAG): An MRI surrogate marker of aging for prostate cancer detection

Image Registration of In Vivo Micro-Ultrasound and Ex Vivo Pseudo-Whole Mount Histopathology Images of the Prostate: A Proof-of-Concept Study

Non-rigid Medical Image Registration using Physics-informed Neural Networks

Comprehensive study of good model training for prostate segmentation in volumetric MRI

Prostate Lesion Detection and Salient Feature Assessment Using Zone-Based Classifiers

Comparison of automatic prostate zones segmentation models in MRI images using U-net-like architectures

CAT-Net: A Cross-Slice Attention Transformer Model for Prostate Zonal Segmentation in MRI