The role of AI in prostate MRI quality and interpretation: Opportunities and challenges

Comparison of a Deep Learning‐Accelerated vs. Conventional T2 ‐Weighted Sequence in Biparametric MRI of the Prostate

(2023) Angela Tong et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Combined model-based and deep learning-based automated 3D zonal segmentation of the prostate on T2-weighted MR images: clinical evaluation

(2022) Olivier Rouvière et al.   EUROPEAN RADIOLOGY

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging

(2022) Takahiro Ueda et al.   RADIOLOGY

Quality in MR reporting (include improvements in acquisition using AI)

(2022) Liang Wang et al.   BRITISH JOURNAL OF RADIOLOGY

Artifact- and content-specific quality assessment for MRI with image rulers

(2022) Ke Lei et al.   MEDICAL IMAGE ANALYSIS

Magnetic resonance imaging contrast enhancement synthesis using cascade networks with local supervision

(2022) Huiqiao Xie et al.   MEDICAL PHYSICS

Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology

(2022) Deepa Darshini Gunashekar et al.   Radiation Oncology

Enhancing MR image segmentation with realistic adversarial data augmentation

(2022) Chen Chen et al.   MEDICAL IMAGE ANALYSIS

Stacked U-Nets with self-assisted priors towards robust correction of rigid motion artifact in brain MRI

(2022) Mohammed A. Al-masni et al.   NEUROIMAGE

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification

(2022) Xin Shu et al.   BRITISH JOURNAL OF RADIOLOGY

Image-based motion artifact reduction on liver dynamic contrast enhanced MRI

(2022) Yunan Wu et al.   Physica Medica-European Journal of Medical Physics

Retrospective motion artifact correction of structural MRI images using deep learning improves the quality of cortical surface reconstructions

(2021) Ben A Duffy et al.   NEUROIMAGE

Deep learning–accelerated T2-weighted imaging of the prostate: Reduction of acquisition time and improvement of image quality

(2021) Sebastian Gassenmaier et al.   EUROPEAN JOURNAL OF RADIOLOGY

ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging

(2021) Tobias Penzkofer et al.   EUROPEAN RADIOLOGY

A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate

(2021) David J. Winkel et al.   INVESTIGATIVE RADIOLOGY

A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion

(2021) Pegah Khosravi et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on MRI for Targeted Biopsy

(2021) Simon John Christoph Soerensen et al.   JOURNAL OF UROLOGY

MC 2 ‐Net: motion correction network for multi‐contrast brain MRI

(2021) Jongyeon Lee et al.   MAGNETIC RESONANCE IN MEDICINE

Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists

(2021) Francesco Giganti et al.   Insights into Imaging

Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience

(2021) Seo Yeon Youn et al.   EUROPEAN JOURNAL OF RADIOLOGY

Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network

(2021) Qing Lyu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Convolutional Neural Networks for Automated Classification of Prostate Multiparametric Magnetic Resonance Imaging Based on Image Quality

(2021) Stefano Cipollari et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging

(2021) Sebastian Gassenmaier et al.   Cancers

Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI

(2021) Andreas M. Hötker et al.   Insights into Imaging

Deep learning-accelerated T2-weighted imaging of the prostate: Impact of further acceleration with lower spatial resolution on image quality

(2021) Eu Hyun Kim et al.   EUROPEAN JOURNAL OF RADIOLOGY

Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate

(2021) Patricia M. Johnson et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction

(2021) Anindo Saha et al.   MEDICAL IMAGE ANALYSIS

Deep learning-based artificial intelligence applications in prostate MRI: brief summary

(2021) Baris Turkbey et al.   BRITISH JOURNAL OF RADIOLOGY

Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI

(2021) Yuchuan Qiao et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Quality of Prostate MRI: Is the PI-RADS Standard Sufficient?

(2020) Jonathan Sackett et al.   ACADEMIC RADIOLOGY

Interreader variability in prostate MRI reporting using Prostate Imaging Reporting and Data System version 2.1

(2020) Giorgio Brembilla et al.   EUROPEAN RADIOLOGY

ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ training

(2020) Maarten de Rooij et al.   EUROPEAN RADIOLOGY

Recent advances in small object detection based on deep learning: A review

(2020) Kang Tong et al.   IMAGE AND VISION COMPUTING

Noninvasive Prediction of High-Grade Prostate Cancer via Biparametric MRI Radiomics

(2020) Lixin Gong et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network

(2020) Weiwei Zong et al.   MEDICAL PHYSICS

Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI

(2020) Muhammad Arif et al.   EUROPEAN RADIOLOGY

Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis

(2020) Renato Cuocolo et al.   EUROPEAN RADIOLOGY

Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning–based filter using convolutional neural network

(2020) M.-L. Kromrey et al.   EUROPEAN RADIOLOGY

Deep‐Learning‐Based Artificial Intelligence for PI‐RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study

(2020) Thomas Sanford et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Interreader Agreement with Prostate Imaging Reporting and Data System Version 2 for Prostate Cancer Detection: A Systematic Review and Meta-Analysis

(2020) Kye Jin Park et al.   JOURNAL OF UROLOGY

Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition

(2020) Mohammed R. S. Sunoqrot et al.   MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE

Measuring the Quality of Diagnostic Prostate Magnetic Resonance Imaging: A Urologist’s Perspective

(2020) Gianluca Giannarini et al.   EUROPEAN UROLOGY

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

(2020) Soan T.M. Duong et al.   MAGNETIC RESONANCE IMAGING

Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB)

(2020) Junchi Liu et al.   MAGNETIC RESONANCE IMAGING

Variability in accuracy of prostate cancer segmentation among radiologists, urologists, and scientists

(2020) Michael Y. Chen et al.   Cancer Medicine

A deep learning framework for quality assessment and restoration in video endoscopy

(2020) Sharib Ali et al.   MEDICAL IMAGE ANALYSIS

Influence of Enema and Dietary Restrictions on Prostate MR Image Quality: A Multireader Study

(2020) Andrei S. Purysko et al.   ACADEMIC RADIOLOGY

Prostate cancer classification with multiparametric MRI transfer learning model

(2019) Yixuan Yuan et al.   MEDICAL PHYSICS

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

(2019) Hamid Abdollahi et al.   Radiologia Medica

Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study

(2019) Satish E. Viswanath et al.   BMC MEDICAL IMAGING

Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2

(2019) Baris Turkbey et al.   EUROPEAN UROLOGY

Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: cross-validation of a machine learning method

(2019) Xiangde Min et al.   EUROPEAN JOURNAL OF RADIOLOGY

Radiomics features measured with multiparametric MRI predict prostate cancer aggressiveness.

(2019) Stefanie J Hectors et al.   JOURNAL OF UROLOGY

High Diagnostic Performance of Short Magnetic Resonance Imaging Protocols for Prostate Cancer Detection in Biopsy-naïve Men: The Next Step in Magnetic Resonance Imaging Accessibility

(2019) Marloes van der Leest et al.   EUROPEAN UROLOGY

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization

(2019) Jussi Toivonen et al.   PLoS One

Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network

(2019) Nader Aldoj et al.   EUROPEAN RADIOLOGY

MRI Gibbs‐ringing artifact reduction by means of machine learning using convolutional neural networks

(2019) Qianqian Zhang et al.   MAGNETIC RESONANCE IN MEDICINE

Unsupervised learning of a deep neural network for metal artifact correction using dual‐polarity readout gradients

(2019) Kinam Kwon et al.   MAGNETIC RESONANCE IN MEDICINE

Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet

(2019) Ruiming Cao et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation

(2019) Qikui Zhu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Adversarial learning for mono- or multi-modal registration

(2019) Jingfan Fan et al.   MEDICAL IMAGE ANALYSIS

Multi-task learning for quality assessment of fetal head ultrasound images

(2019) Zehui Lin et al.   MEDICAL IMAGE ANALYSIS

Detecting Prostate Cancer with Deep Learning for MRI: A Small Step Forward

(2019) Anwar R. Padhani et al.   RADIOLOGY

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment

(2019) Patrick Schelb et al.   RADIOLOGY

Prostate Cancer Detection using Deep Convolutional Neural Networks

(2019) Sunghwan Yoo et al.   Scientific Reports

Imaging Facilities' Adherence to PI-RADS v2 Minimum Technical Standards for the Performance of Prostate MRI

(2018) Steven J. Esses et al.   ACADEMIC RADIOLOGY

National implementation of multi-parametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting

(2018) Mrishta Brizmohun Appayya et al.   BJU INTERNATIONAL

Support Vector Machines (SVM) classification of prostate cancer Gleason score in central gland using multiparametric magnetic resonance images: A cross-validated study

(2018) Jiance Li et al.   EUROPEAN JOURNAL OF RADIOLOGY

Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings

(2018) Rakesh Shiradkar et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI

(2018) Enhao Gong et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI

(2018) Yang Song et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Weakly-supervised convolutional neural networks for multimodal image registration

(2018) Yipeng Hu et al.   MEDICAL IMAGE ANALYSIS

Can computer-aided diagnosis assist in the identification of prostate cancer on prostate MRI? a multi-center, multi-reader investigation

(2018) Sonia Gaur et al.   Oncotarget

A Deep Learning-Based Approach for the Detection and Localization of Prostate Cancer in T2 Magnetic Resonance Images

(2018) Ruba Alkadi et al.   JOURNAL OF DIGITAL IMAGING

Fully automatic segmentation on prostate MR images based on cascaded fully convolution network

(2018) Yi Zhu et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): a prospective, multicentre, paired diagnostic study

(2018) Olivier Rouvière et al.   LANCET ONCOLOGY

Multiparametric magnetic resonance imaging of the prostate with computer-aided detection: experienced observer performance study

(2017) Valentina Giannini et al.   EUROPEAN RADIOLOGY

Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer

(2017) Jing Wang et al.   EUROPEAN RADIOLOGY

Learning a variational network for reconstruction of accelerated MRI data

(2017) Kerstin Hammernik et al.   MAGNETIC RESONANCE IN MEDICINE

Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis

(2017) Xiaohuan Cao et al.   MEDICAL IMAGE ANALYSIS

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI

(2017) Xin Yang et al.   MEDICAL IMAGE ANALYSIS

A supervoxel-based segmentation method for prostate MR images

(2017) Zhiqiang Tian et al.   MEDICAL PHYSICS

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning

(2017) Xinggang Wang et al.   Scientific Reports

PI-RADS Prostate Imaging – Reporting and Data System: 2015, Version 2

(2016) Jeffrey C. Weinreb et al.   EUROPEAN UROLOGY

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching

(2016) Yanrong Guo et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

An imaging-based approach predicts clinical outcomes in prostate cancer through a novel support vector machine classification

(2016) Yu-Dong Zhang et al.   Oncotarget

Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

(2015) Andreas Wibmer et al.   EUROPEAN RADIOLOGY

Magnetic Resonance Imaging in Active Surveillance of Prostate Cancer: A Systematic Review

(2015) Ivo G. Schoots et al.   EUROPEAN UROLOGY

Robust inverse-consistent affine CT–MR registration in MRI-assisted and MRI-alone prostate radiation therapy

(2015) David Rivest-Hénault et al.   MEDICAL IMAGE ANALYSIS

Population-based prediction of subject-specific prostate deformation for MR-to-ultrasound image registration

(2015) Yipeng Hu et al.   MEDICAL IMAGE ANALYSIS

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

(2015) Hualiang Zhong et al.   PHYSICS IN MEDICINE AND BIOLOGY

Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness

(2015) A Vignati et al.   PHYSICS IN MEDICINE AND BIOLOGY

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

(2015) Duc Fehr et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Magnetic Resonance–invisible Versus Magnetic Resonance–visible Prostate Cancer in Active Surveillance: A Preliminary Report on Disease Outcomes

(2015) Seyed Saeid Dianat et al.   UROLOGY

Prostate MRI: Access to and Current Practice of Prostate MRI in the United States

(2014) James L. Leake et al.   Journal of the American College of Radiology

Final Gleason Score Prediction Using Discriminant Analysis and Support Vector Machine Based on Preoperative Multiparametric MR Imaging of Prostate Cancer at 3T

(2014) Fusun Citak-Er et al.   Biomed Research International

Prostate Cancer: Can Multiparametric MR Imaging Help Identify Patients Who Are Candidates for Active Surveillance?

(2013) Baris Turkbey et al.   RADIOLOGY

ESUR prostate MR guidelines 2012

(2012) Jelle O. Barentsz et al.   EUROPEAN RADIOLOGY

Prostate Cancer Localization Using Multiparametric MRI based on Semisupervised Techniques With Automated Seed Initialization

(2012) Yusuf Artan et al.   IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE

MR to ultrasound registration for image-guided prostate interventions

(2010) Yipeng Hu et al.   MEDICAL IMAGE ANALYSIS

Supervised and unsupervised methods for prostate cancer segmentation with multispectral MRI

(2010) Sedat Ozer et al.   MEDICAL PHYSICS

Compressed Sensing MRI

(2008) M. Lustig et al.   IEEE SIGNAL PROCESSING MAGAZINE

Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information

(2008) Stefan Klein et al.   MEDICAL PHYSICS