Expert Consensus on CT Image Database Construction and Quality Control for Colorectal Cancer
10.3969/j.issn.1005-5185.2025.01.001
- VernacularTitle:结直肠癌CT影像数据库构建及质量控制专家共识
- Author:
Junlin ZHOU
;
Nan HONG
;
Huimao ZHANG
;
Min CHEN
;
Shiyuan LIU
- Collective Name:Artificial Intelligence Working Group of Chinese Society of Radiology Chinese Medical Association
- Publication Type:Journal Article
- Keywords:
Colorectal neoplasms;
Database;
Tomography,X-ray computed;
Quality control;
Expert consensus
- From:
Chinese Journal of Medical Imaging
2025;33(1):1-9
- CountryChina
- Language:Chinese
-
Abstract:
Colorectal cancer is one of the most common malignant tumors of the digestive system in clinical practice.The early detection of colorectal cancer based on artificial intelligence and its further assistance in clinical diagnosis and treatment hold significant clinical importance for achieving long-term benefits for patients.The development and validation of artificial intelligence software rely on high-quality,large-volume,and annotated colorectal cancer imaging datasets.This paper aims to provide a reference for constructing a high-quality colorectal cancer CT database,taking the construction of the database as an example.It discusses the complete process of database establishment,including database description,lesion annotation and storage,database quality evaluation and maintenance.The purpose is to ensure the high quality and exploitability of the source materials in the database,promote the sustainable and healthy development of the medical imaging artificial intelligence industry ecosystem,and accelerate the research,development,and application of industries related to artificial intelligence in colorectal cancer CT imaging.
