BACKGROUND AND PURPOSE: Radiomics analysis has emerged as a promising approach to aid in cancer diagnosis and treatment. However, radiomics research currently lacks standardization, and radiomics features can be highly dependent on acquisition and pr...
Exploring the clinical significance of employing deep learning methodologies on ultrasound images for the development of an automated model to accurately identify pleomorphic adenomas and Warthin tumors in salivary glands. A retrospective study was c...
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.
Journal of computational biology : a journal of computational molecular cell biology
Mar 28, 2025
Gleason grading of prostate histopathology images is widely used by pathologists for diagnosis and prognosis. Spatial characteristics of cell and tissues through staining images is essential for accurate grading of prostate cancer. Although considera...
BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the staging systems due to inter-observer variability and time constraints. While digital pathology offers artificial intelligence-driven solutions, exist...
Diabetic retinopathy (DR) is a chronic condition associated with diabetes that can lead to vision impairment and, if not addressed, may progress to irreversible blindness. Consequently, it is essential to detect pathological changes in the retina to ...
Multimodal medical image fusion is crucial for enhancing diagnostic accuracy by integrating complementary information from different imaging modalities. Current fusion techniques face challenges in effectively combining heterogeneous features while p...
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.
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