The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …

Colonoscopy is an effective technique for detecting colorectal polyps, which are highly
related to colorectal cancer. In clinical practice, segmenting polyps from colonoscopy …

Abstract Large Vision-Language Models (LVLMs) have demonstrated remarkable
capabilities in various multimodal tasks. However their potential in the medical domain …

Accurate computer-aided polyp detection and segmentation during colonoscopy
examinations can help endoscopists resect abnormal tissue and thereby decrease chances …

Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In
practice, it is difficult to find annotated medical images with corresponding segmentation …

The success of pretrain-finetune paradigm brings about the release of numerous model
weights. In this case, merging models finetuned on different tasks to enable a single model …

Effective fusion of global and local multi-scale features is crucial for medical image
classification. Medical images have many noisy, scattered features, intra-class variations …

Computer-aided detection, localization, and segmentation methods can help improve
colonoscopy procedures. Even though many methods have been built to tackle automatic …

Since the era of deep learning, convolutional neural networks (CNNs) and vision
transformers (ViTs) have been extensively studied and widely used in medical image …