Abstract Numerous Deep Learning (DL) classification models have been developed for a
large spectrum of medical image analysis applications, which promises to reshape various …

Medical Image Analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …

Numerous Deep Learning (DL) classification models have been developed for a large
spectrum of medical image analysis applications, which promises to reshape various facets …

Multi-modal data fusion for effective feature representation in machine learning is
challenging due to intrinsic biases present within and across different modalities. Existing …

Introduction With increasing use of robotic surgical adjuncts, artificial intelligence and
augmented reality in neurosurgery, the automated analysis of digital images and videos …

Integrating Minimally Invasive Surgery (MIS) with robotic systems has revolutionized surgical
procedures by enhancing precision, reducing patient discomfort, and shortening recovery …

Medical image analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …

Despite their impressive performance in various surgical scene understanding tasks, deep
learning-based methods are frequently hindered from deploying to real-world surgical …

In the unattended industrial environment, the piping leakage detection algorithm based on
the combination of image detection and machine learning has the advantages of high …

As domain shift hinders deep learning models' performance on medical image analysis,
Domain Generalization (DG) has been proposed to enhance the generalization capability …