The importance of gastric cancer (GC) and the role of deep learning techniques in categorizing GC histopathology images have recently increased. Identifying the drawbacks of traditional deep learning models, including lack of interpretability, inabil...
BACKGROUND: Emerging evidence underscores smooth muscle hyperplasia and hypertrophy, rather than fibrosis, as the defining characteristics of fibrostenotic lesions in Crohn disease (CD). However, non-invasive methods for quantifying these muscular ch...
Polyp segmentation is crucial in computer-aided diagnosis but remains challenging due to the complexity of medical images and anatomical variations. Current state-of-the-art methods struggle with accurate polyp segmentation due to the variability in ...
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...
OBJECTIVE: This study aims to assess diagnostic performance of high-resolution dynamic contrast-enhanced (DCE) MRI with deep learning-based compressed sensing and super-resolution (DLCS-SR) reconstruction for identifying microadenomas.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 13, 2025
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. However, in clinical settings without manual annotations, assessing segmenta...
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...
Despite their effectiveness, current deep learning models face challenges with images coming from different domains with varying appearance and content. We introduce SegCLR, a versatile framework designed to segment images across different domains, e...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 12, 2025
Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is labor-intensive and prone to variability. Despite advancements in MRI technology, there remains a significant need for automated methods that can reli...
The exploration of deep learning techniques for predicting various biological characteristics of endometrial cancer (EC) is of significant importance. The objective of this study was to develop an optimized radiomics scheme combining multiparametric ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.