Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 16, 2025
Carotid ultrasound image segmentation and classification are crucial in assessing the severity of carotid plaques which serve as a major cause of ischemic stroke. Although many methods are employed for carotid plaque segmentation and classification, ...
Automated detection of emotional states through brain-computer interfaces (BCIs) offers significant potential for enhancing user experiences and personalizing services across domains such as mental health, adaptive learning and interactive entertainm...
Right ventricular dysfunction (RVD) is strongly associated with increased mortality in patients with acute pulmonary embolism (PE), making its early detection crucial. Identifying RVD risk factors rapidly, accurately, and economically within the acut...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 8, 2025
Medical self-supervised learning eliminates the reliance on labels, making feature extraction simple and efficient. The intricate design of pretext tasks in single-modal self-supervised analysis presents challenges, however, compounded by an excessiv...
Postnatal adverse outcomes can often be explained and predicted by the pathological evaluation of the placenta after a pregnancy. However, placenta whole-slide image (WSI) analysis is not performed systematically due to the specialized skills require...
Delineation of multiple organs in murine µCT images is crucial for preclinical studies but requires manual volumetric segmentation, a tedious and time-consuming process prone to inter-observer variability. Automatic deep learning-based segmentation c...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 1, 2025
Recent advancements in deep learning techniques have contributed to developing improved polyp segmentation methods, thereby aiding in the diagnosis of colorectal cancer and facilitating automated surgery like endoscopic submucosal dissection (ESD). H...
Extracting richer emotional representations from raw speech is one of the key approaches to improving the accuracy of Speech Emotion Recognition (SER). In recent years, there has been a trend in utilizing self-supervised learning (SSL) for extracting...
Segmenting abnormalities is a leading problem in medical imaging. Using machine learning for segmentation generally requires manually annotated segmentations, demanding extensive time and resources from radiologists. We propose a weakly supervised ap...
Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algor...
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