Evaluating large artery atherosclerosis is critical for predicting and preventing ischemic strokes. Ultrasonographic assessment of the carotid arteries is the preferred first-line examination due to its ease of use, noninvasive, and absence of radiat...
In principle, ML/AI-based algorithms should enable rapid and accurate cell segmentation in high-throughput settings. However, reliance on large training datasets, human input, computational expertise, and limited generalizability has prevented this g...
Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging te...
In this study, we introduce a groundbreaking deep learning (DL) model designed for the precise task of classifying common diseases in tea leaves, leveraging advanced image analysis techniques. Our model is distinguished by its complex multi-layer arc...
The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment strategies for each ...
An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enabling accurate prediction of clinical pregnancy outcomes in single embryo transfer procedures. Three ...
OBJECTIVE: With a growing need for ultra-widefield fundus (UWF) fundus photographs in clinics and AI development, image quality assessment (IQA) of UWF fundus photographs is an important preceding step for accurate diagnosis and clinical interpretati...
Biomedical physics & engineering express
May 21, 2025
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is the leading cause of dementia worldwide and remains incurable once it begins. Therefore, early and accurate diagnosis is essential for effective intervention. Leveraging recent ad...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
May 20, 2025
OBJECTIVES: We propose a multi-scale jaw cyst segmentation model, AConvLSTM U-Net, which is based on bidirectional dense connections and attention mechanisms to achieve accurate automatic segmentation of mandibular cyst images.
A layman in health systems is a person who doesn't have any knowledge about health data i.e., X-ray, MRI, CT scan, and health examination reports, etc. The motivation behind the proposed invention is to help laymen to make medical images understandab...
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