S-Space College of Medicine/School of Medicine (의과대학/대학원) Dept. of Radiation Applied Life Science (대학원 협동과정 방사선응용생명과학전공) Journal Papers (저널논문_방사선응용생명과학전공)
Computer-aided detection of colonic polyps at CT colonography using a Hessian matrix-based algorithm: preliminary study
- Issue Date
- American Roentgen Ray Society
- AJR 2007; 189:41-51
- Adult ; Aged ; Colonic Polyps/*radiography ; Colonography, Computed Tomographic/*methods ; Female ; Humans ; Male ; Middle Aged ; Pattern Recognition, Automated/*methods ; Pilot Projects ; Radiographic Image Interpretation, Computer-Assisted/*methods ; Reproducibility of Results ; Sensitivity and Specificity ; Algorithms ; Artificial Intelligence
- OBJECTIVE: The purpose of our study was to develop a Hessian matrix-based computer-aided detection (CAD) algorithm for polyp detection on CT colonography (CTC) and to analyze its performance in a high-risk population. SUBJECTS AND METHODS: The CTC data sets of 35 patients with at least one colonoscopically proven polyp were interpreted with a Hessian matrix-based CAD algorithm, which was designed to depict bloblike structures protruding into the lumen. Our gold standard was a combination of segmental unblinded optical colonoscopy and retrospective unblinded consensus review by two radiologists. Sensitivity of CAD for polyp detection was evaluated on both per-polyp and per-patient bases. The average number of false-positive detections was calculated, and the causes of false-positives and false-negatives were analyzed. RESULTS: Ninety-four polyps were identified on colonoscopy. Forty-six polyps were smaller than 6 mm and 48 were 6 mm or larger. Seventy-five (79.8%) of these 94 polyps were identified by radiologists in a retrospective review. When colonoscopy was used as a standard of reference, the sensitivity of CAD was 77.1% for polyps 6 mm or larger. For large polyps (> or = 6 mm) that could be identified on retrospective review, the CAD algorithm achieved sensitivities of 92.5% (37/40) and 91.7% (22/24), respectively, on per-polyp and per-patient bases. There were an average of 5.5 false-positive detections per patient and 3.1 false-positive detections per data set for CAD. The two most frequent causes of false-positives on CAD were prominent or converging fold (78/191) and feces (50/191). Of the three polyps 6 mm or larger that were missed by CAD, two had a flat appearance on colonoscopy and the remaining one was located in the narrow area between the rectal tube and the rectal wall. CONCLUSION: A Hessian matrix-based CAD algorithm for CTC has the potential to depict polyps larger than or equal to 6 mm with high sensitivity and an acceptable false-positive rate.
- 1546-3141 (Electronic)
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