AIMC Topic: Prostate
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Machine Learning to Predict Prostate Artery Embolization Outcomes.
Cardiovascular and interventional radiology
Jun 19, 2024
PURPOSE: This study leverages pre-procedural data and machine learning (ML) techniques to predict outcomes at one year following prostate artery embolization (PAE).
Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent.
The Journal of urology
Jun 11, 2024
PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care metho...
ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.
Magnetic resonance in medicine
Jun 9, 2024
PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.
Diffusion Magnetic Resonance Imaging
Prostate
Supervised Machine Learning
Image Interpretation, Computer-Assisted
Male
Middle Aged
Humans
Deep Learning
Neural Networks, Computer
Image Processing, Computer-Assisted
Algorithms
Magnetic Resonance Imaging
Computer Simulation
Least-Squares Analysis
Prostatic Neoplasms
Verification of image quality improvement by deep learning reconstruction to 1.5 T MRI in T2-weighted images of the prostate gland.
Radiological physics and technology
Jun 8, 2024
This study aimed to evaluate whether the image quality of 1.5 T magnetic resonance imaging (MRI) of the prostate is equal to or higher than that of 3 T MRI by applying deep learning reconstruction (DLR). To objectively analyze the images from the 13 ...
Assessing deep learning reconstruction for faster prostate MRI: visual vs. diagnostic performance metrics.
European radiology
May 9, 2024
OBJECTIVE: Deep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the ...
PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI.
La Radiologia medica
May 3, 2024
PURPOSE: High PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and th...
Diagnostic Utility of Artificial Intelligence-assisted Transperineal Biopsy Planning in Prostate Cancer Suspected Men: A Prospective Cohort Study.
European urology focus
Apr 29, 2024
BACKGROUND AND OBJECTIVE: Accurate magnetic resonance imaging (MRI) reporting is essential for transperineal prostate biopsy (TPB) planning. Although approved computer-aided diagnosis (CAD) tools may assist urologists in this task, evidence of improv...
Single-port robot-assisted radical prostatectomy.
World journal of urology
Apr 20, 2024
PURPOSE: To provide a comprehensive update on the different techniques and outcomes of contemporary Single-Port (SP) Robotic Radical Prostatectomy (RARP) approaches.
Advantage of whole-mount histopathology in prostate cancer: current applications and future prospects.
BMC cancer
Apr 11, 2024
BACKGROUND: Whole-mount histopathology (WMH) has been a powerful tool to investigate the characteristics of prostate cancer. However, the latest advancement of WMH was yet under summarization. In this review, we offer a comprehensive exposition of cu...
Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy.
Physics in medicine and biology
Apr 9, 2024
In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast...
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