Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer.
This study investigates the frontiers of intelligent colonoscopy techniques and their …

The medical image partition model has a wide range of application prospects in medical
diagnosis and treatment and has become an important auxiliary method to improve the …

Existing semi-supervised polyp segmentation methods assume that unlabeled images are
positive, containing lesions to be annotated, while neglecting negative samples that are …

Segment Anything Model 2 (SAM 2) has emerged as a powerful tool for video object
segmentation and tracking anything. Key components of SAM 2 that drive the impressive …

The application of Contrastive Language-Image Pre-training (CLIP) in Weakly Supervised
Semantic Segmentation (WSSS) research powerful cross-modal semantic understanding …

Dental panoramic X-ray imaging, due to its high cost-effectiveness and low radiation dose,
has become a widely used diagnostic tool in dentistry. Accurate tooth segmentation is …

Despite the evident advantages of variants of UNet in medical image segmentation, these
methods still exhibit limitations in the extraction of foreground, background, and boundary …

As the successor to the Segment Anything Model (SAM), the Segment Anything Model 2
(SAM2) not only improves performance in image segmentation but also extends its …

Early and accurate polyp segmentation is crucial for the diagnosis and treatment of
colorectal cancer. However, polyp segmentation faces many challenges: different polyp …

Long-sequence causal reasoning seeks to uncover causal relationships within extended
time series data but is hindered by complex dependencies and the challenges of validating …