@inproceedings{a52ce925487245649d6da332d8bf2bd9,
title = "Computer-aided polyp detection for laxative-free CT colonography",
abstract = "Image-based colon cleansing performed on fecal-tagged CT colonography (CTC) allows the laxative-free detection of colon polyps, unlike optical colonoscopy (OC), the preferred screening method. Compared to OC, CTC increases the patient comfort and compliance with colon cancer screening. However, laxative-free CTC introduces many challenges and imaging artifacts, such as poorly and heterogeneously tagged stool, thin stool close to the colon walls, pseudoenhancement of colon tissue, and partial volume effect. We propose an automated algorithm to subtract stool prior to the computer aided detection of colonic polyps. The method is locally adaptive and combines intensity, shape and texture analysis with probabilistic optimization. Results show stool removal accuracy on data with various bowel preparations. The automatic detection of polyps using our CAD system on cathartic-free data improves significantly from 70% to 85% true positive rate at 5.75 false positives/scan.",
keywords = "CTC, cleansing, colon cancer, heterogeneous stool, laxative-free, polyp detection",
author = "Neil Panjwani and Linguraru, {Marius George} and Fletcher, {Joel G.} and Summers, {Ronald M.}",
year = "2012",
doi = "10.1007/978-3-642-28557-8_3",
language = "English (US)",
isbn = "9783642285561",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "18--26",
booktitle = "Abdominal Imaging",
note = "3rd International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 ; Conference date: 18-09-2011 Through 18-09-2011",
}