This study is a prospective,multi-center and observational clinical study.Investigators would like to innovatively construct a "trinity" database of colorectal tubular adenomas based on white light - magnifying chromo - pathological images.It simulates the decision - making logic of doctors, and based on the multimodal endoscopic LAFEQ method previously proposed, develop a multimodal deep - learning diagnostic model for colon adenomas and an interpretable risk prediction model for intestinal adenomas. While achieving high - precision auxiliary treatment decisions, clearly present the decision - making basis, and break through the limitation of poor interpretability of previous medical imaging AI models.

Inclusion Criteria:

• Patients aged ≥ 18 years, who need to undergo colonoscopy, regardless of gender.
• Voluntarily sign the informed consent form
• Promise to abide by the research procedures and cooperate in the implementation of the entire research process.

Exclusion Criteria:

• Patients who has a history of abdominal or pelvic surgery or radiotherapy in the past;
• Patients who has definite active lower gastrointestinal bleeding.
• Existing or suspected hereditary colorectal polyposis, inflammatory bowel disease;
• Uncontrolled hypertension (systolic blood pressure > 160 mmHg or diastolic blood pressure > 95 mmHg after standardized treatment)
• There is a history of stroke, coronary artery disease, or vascular disease;
• Pregnant;
• Intestinal preparation cannot be carried out.

Patients withonic col adenomas or polyps