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Multiparametric Magnetic Resonance Imaging

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Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

Clinical breast cancer
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

The Prostate
BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate biopsies without missing clinically significant prostate cancers (csPCa). The utility of multiparametric magnetic resonance imaging (mpMRI) in detecting...

Development and head-to-head comparison of machine-learning models to identify patients requiring prostate biopsy.

BMC urology
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...

Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.

Sensors (Basel, Switzerland)
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
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
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
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)
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
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...