As large medical imaging datasets become widely available, researchers are increasingly turning to artificial intelligence to ...
In the era of data-driven medicine, biomedical imaging has evolved from a purely diagnostic tool to a cornerstone of precision healthcare. The confluence of deep learning (DL) and biomedical image ...
Abstract: Medical image segmentation, especially in multi-organ segmentation, requires accurate delineation of small targets and complex anatomical structures. Traditional models often encounter ...
Abstract: Image segmentation stands as a pivotal challenge in the realm of computer vision. Although in recent times, deep learning-based segmentation methods have emerged as front-runners in ...
Background: Coronary artery segmentation, Lesion Identification and Measurement (CASLIM) on XRA images on X-ray angiography (XRA) are performed by cardiologists. Aims: The study, CASLIM aims to ...
Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8573, Japan ...
Neural networks are powerful tools for processing visual inputs, but precisely how this processing is performed remains unclear. We introduce a recurrent neural network that can perform simple image ...
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