A colon polyp image processing method and apparatus and a system are disclosed in the embodiments of this application, to detect a position of a polyp in real time and determine a property of the polyp, thereby improving the processing efficiency of a polyp image. Embodiment of this application...
Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. To be an effective system, it is important to detect additional polyps that may be easily missed by endoscopists. Sessile serrated lesions (SSLs) are a precursor to colorectal cancer with a...
We evaluate the performance of our method on several popular benchmark datasets for polyp segmentation, Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, and ETIS-LARIBPOLYPDB showing that it achieves state-of-the-art results in terms of mean Dice coefficient, Jaccard index, Precision, Recall, and ...
Recently emerged SAM-Med2D represents a state-of-the-art advancement in medical image segmentation. Through fine-tuning the Large Visual Model, Segment Anything Model (SAM), on extensive medical datasets, it has achieved impressive results in cross-modal medical image segmentation. However, its reli...
A colon polyp image processing method and apparatus, and a system, being used for discovering the position of a polyp in real time and determining the characteristics of the polyp, thereby improving the efficiency of processing a polyp image. The colon polyp image processing method comprises: perf...
Pixel Values = "create a vector from RGB values of the image" In fact, to get good results from BOW features, people often derive individual features using relatively complicated algorithms. In the project athttp://vision.stanford.edu/projects/totalscene/index.html(paper in reference #1), the...
Despite the availability of powerful segmentation models, two challenges still impede the accuracy of polyp segmentation algorithms. Firstly, during a colonoscopy, physicians frequently adjust the orientation of the colonoscope tip to capture underlying lesions, resulting in viewpoint changes in the ...
We evaluate the performance of our method on several popular benchmark datasets for polyp segmentation, Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, and ETIS-LARIBPOLYPDB showing that it achieves state-of-the-art results in terms of mean Dice coefficient, Jaccard index, Precision, Recall, and ...
of immature SD, which could better represent the metastatic and mesenchymal CRC phenotype13. Histologically, the clinical significance of SD has been demonstrated in the breast14, cervix15and esophagus16; however, it has been most extensively studied in cancers of the colon and rectum17,18,19,20...
A total of 80 patients’ 3,865 images (with an average size of 1280 × 1024) recorded during the colonoscopy examination on the workstations in Renji Hospital are produced in the Endo dataset. Four types of lesions, i.e., ulcer, erosion, polyp, and tumor, are included, which are...