AIMC Topic: Multiparametric Magnetic Resonance Imaging
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Development and head-to-head comparison of machine-learning models to identify patients requiring prostate biopsy.
BMC urology
May 16, 2021
BACKGROUND: Machine learning has many attractive theoretic properties, specifically, the ability to handle non predefined relations. Additionally, studies have validated the clinical utility of mpMRI for the detection and localization of CSPCa (Gleas...
Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.
The Journal of urology
Apr 21, 2021
PURPOSE: Targeted biopsy improves prostate cancer diagnosis. Accurate prostate segmentation on magnetic resonance imaging (MRI) is critical for accurate biopsy. Manual gland segmentation is tedious and time-consuming. We sought to develop a deep lear...
Software
Prospective Studies
Retrospective Studies
Reproducibility of Results
Humans
Image Processing, Computer-Assisted
Multimodal Imaging
Prostatic Neoplasms
Ultrasonography, Interventional
Male
Deep Learning
Time Factors
Proof of Concept Study
Image-Guided Biopsy
Magnetic Resonance Imaging, Interventional
Multiparametric Magnetic Resonance Imaging
Prostate
Feasibility Studies
Datasets as Topic
Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.
Sensors (Basel, Switzerland)
Apr 12, 2021
The accuracy in diagnosing prostate cancer (PCa) has increased with the development of multiparametric magnetic resonance imaging (mpMRI). Biparametric magnetic resonance imaging (bpMRI) was found to have a diagnostic accuracy comparable to mpMRI in ...
Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy.
Epilepsia
Apr 5, 2021
OBJECTIVE: Improving the identification of the epileptogenic zone and associated seizure-spreading regions represents a significant challenge. Innovative brain-imaging modalities tracking neurovascular dynamics during seizures may provide new disease...
Automated detection of critical findings in multi-parametric brain MRI using a system of 3D neural networks.
Scientific reports
Mar 25, 2021
With the rapid growth and increasing use of brain MRI, there is an interest in automated image classification to aid human interpretation and improve workflow. We aimed to train a deep convolutional neural network and assess its performance in identi...
Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer Using 3-T Multiparametric Magnetic Resonance Imaging.
Journal of magnetic resonance imaging : JMRI
Mar 12, 2021
BACKGROUND: Several deep learning-based techniques have been developed for prostate cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but few of them have been rigorously evaluated relative to radiologists' performance ...
Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging.
Abdominal radiology (New York)
Feb 12, 2021
INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have b...
Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition.
Osteoarthritis and cartilage
Feb 3, 2021
BACKGROUND: Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely disabling disease with high prevalence and considerable socioeconomic and individual burden. Early, potentially reversible cartilage degeneration is cha...
Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning.
Scientific reports
Nov 23, 2020
Differentiating pseudoprogression from true tumor progression has become a significant challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a potential treatment delay for patients with early glioma recurren...
A 3D-2D Hybrid U-Net Convolutional Neural Network Approach to Prostate Organ Segmentation of Multiparametric MRI.
AJR. American journal of roentgenology
Nov 10, 2020
OBJECTIVE: Prostate cancer is the most commonly diagnosed cancer in men in the United States with more than 200,000 new cases in 2018. Multiparametric MRI (mpMRI) is increasingly used for prostate cancer evaluation. Prostate organ segmentation is an ...
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