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Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach by Prasan Kumar Sahoo; Pushpanjali Gupta; Ying-Chieh Lai; Sum-Fu Chiang; Jeng-Fu You; Djeane Debora Onthoni; Yih-Jong Chern is a Medicine article available to read on EtoBox.
What is Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach about?
Abdominal computed tomography (CT) is a frequently used imaging modality for evaluating gastrointestinal diseases. The detection of colorectal cancer is often realized using CT before a more invasive colonoscopy. When a CT exam is performed for indications other than colorectal evaluation, the tortuous structure of the long, tubular colon makes it difficult to analyze the colon carefully and thoroughly. In addition, the sensitivity of CT in detecting colorectal cancer is greatly dependent on the size of the tumor. Missed incidental colon cancers using CT are an emerging problem for clinicians and radiologists; consequently, the automatic localization of lesions in the CT images of unprepared bowels is needed. Therefore, this study used artificial intelligence (AI) to localize colorectal cancer in CT images. We enrolled 190 colorectal cancer patients to obtain 1558 tumor slices annotated by radiologists and colorectal surgeons. The tumor sites were double-confirmed via colonoscopy or other related examinations, including physical examination or image study, and the final tumor sites were obtained from the operation records if available. The localization and training models used were
Who reads Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach?
It is typically read by researchers, students, and practitioners in Medicine.
- Author
- Prasan Kumar Sahoo; Pushpanjali Gupta; Ying-Chieh Lai; Sum-Fu Chiang; Jeng-Fu You; Djeane Debora Onthoni; Yih-Jong Chern
- Publisher
- MDPI AG
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)