This paper introduces a novel convolutional neural network model with an attention mechanism to advance Alzheimer disease (AD) classification using Magnetic Resonance Imaging (MRI). The model architecture is meticulously crafted to enhance feature ex...
OBJECTIVE: This study aims to establish a large degenerative cervical myelopathy cohort and develop deep learning models for predicting cervical canal stenosis from sagittal T2-weighted MRI.
BACKGROUND: Schizophrenia (SCH) is a complex neurodevelopmental disorder, whose pathogenesis is not fully elucidated. This article aims to reveal disease-specific brain structural and functional changes and their potential genetic basis by analyzing ...
BACKGROUND: Distinguishing between benign and malignant testicular lesions on clinical magnetic resonance imaging (MRI) is crucial for guiding treatment planning. However, conventional MRI-based radiomics to identify testicular cancer requires expert...
Bulletin of experimental biology and medicine
Mar 28, 2025
The aim of this study was to evaluate the quality of manual segmentation of cerebral infarction lesions in experimental animals with modeled brain infarct based on magnetic resonance imaging compared to an automated artificial intelligence approach. ...
BACKGROUND AND PURPOSE: Biochemical recurrence (BCR) following prostate cancer (PCa) treatment is a significant indicator of metastasis and mortality. Early prediction of BCR can guide treatment decisions, and optimize patient management strategies. ...
BACKGROUND: To evaluate the performance of a deep learning reconstruction (DLR) based on Adaptive-Compressed sensing (CS)-Network for brain MRI and validate it in a clinical setting.
OBJECTIVE: This systematic review explores key quantitative and semi-quantitative MRI-based scoring systems for arthritis biomarkers, focusing on their potential for automation through AI.
Diagnostic and interventional radiology (Ankara, Turkey)
Mar 26, 2025
PURPOSE: This study aimed to evaluate the effectiveness of artificial intelligence (AI) in diagnosing focal nodular hyperplasia (FNH) of the liver using magnetic resonance imaging (MRI) and compare its performance with that of radiologists.
International journal of radiation oncology, biology, physics
Mar 26, 2025
PURPOSE: Evaluation of artificial intelligence (AI) algorithms for prostate segmentation is challenging because ground truth is lacking. We aimed to: (1) create a reference standard data set with precise prostate contours by expert consensus, and (2)...
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