The Experts below are selected from a list of 1425 Experts worldwide ranked by ideXlab platform
Ronald M Summers - One of the best experts on this subject based on the ideXlab platform.
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visual phrase learning and its application in Computed Tomographic Colonography
Medical Image Computing and Computer-Assisted Intervention, 2013Co-Authors: Shijun Wang, Matthew Mckenna, Zhuoshi Wei, Jiamin Liu, Peter Liu, Ronald M SummersAbstract:In this work, we propose a visual phrase learning scheme to learn an optimal visual composite of anatomical components/parts from CT Colonography images for computer-aided detection. The key idea is to utilize the anatomical parts of human body from medical images and associate them with biological targets of interest (organs, cancers, lesions, etc.) for joint detection and recognition. These anatomical parts of the human body are not necessarily near each other regarding their physical locations, and they serve more like a human body navigation system for detection and recognition. To show the effectiveness of the proposed learning scheme, we applied it to two sub-problems in Computed Tomographic Colonography: teniae detection and classification of colorectal polyp candidates. Experimental results showed its efficacy.
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MICCAI (1) - Visual phrase learning and its application in Computed Tomographic Colonography.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Inte, 2013Co-Authors: Shijun Wang, Matthew Mckenna, Zhuoshi Wei, Jiamin Liu, Peter Liu, Ronald M SummersAbstract:In this work, we propose a visual phrase learning scheme to learn an optimal visual composite of anatomical components/parts from CT Colonography images for computer-aided detection. The key idea is to utilize the anatomical parts of human body from medical images and associate them with biological targets of interest (organs, cancers, lesions, etc.) for joint detection and recognition. These anatomical parts of the human body are not necessarily near each other regarding their physical locations, and they serve more like a human body navigation system for detection and recognition. To show the effectiveness of the proposed learning scheme, we applied it to two sub-problems in Computed Tomographic Colonography: teniae detection and classification of colorectal polyp candidates. Experimental results showed its efficacy.
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computer vision approach to detect colonic polyps in Computed Tomographic Colonography
Proceedings of SPIE, 2012Co-Authors: Matthew Mckenna, Shijun Wang, Tan B Nguyen, Joseph E Burns, Nicholas Petrick, Berkman Sahiner, Ronald M SummersAbstract:In this paper, we present evaluation results for a novel colonic polyp classification method for use as part of a Computed Tomographic Colonography (CTC) computer-aided detection (CAD) algorithm. Inspired by the interpretative methodology of radiologists using 3D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. First, we generated an initial list of polyp candidates using an existing CAD system. For each of these candidates, we created a video composed of a series of intraluminal, volume-rendered images focusing on the candidate from multiple viewpoints. These videos illustrated the shape of the polyp candidate and gathered contextual information of diagnostic importance. We calculated the histogram of oriented gradients (HOG) feature on each frame of the video and utilized a support vector machine for classification. We tested our method by analyzing a CTC data set of 50 patients from three medical centers. Our proposed video analysis method for polyp classification showed significantly better performance than an approach using only the 2D CT slice data. The areas under the ROC curve for these methods were 0.88 (95% CI: [0.84, 0.91]) and 0.80 (95% CI: [0.75, 0.84]) respectively (p=0.0005).
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computer aided marginal artery detection on Computed Tomographic Colonography
Proceedings of SPIE, 2012Co-Authors: Zhuoshi Wei, Shijun Wang, Jiamin Liu, Jianhua Yao, Ronald M SummersAbstract:Computed Tomographic Colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. The marginal artery of the colon, also known as the marginal artery of Drummond, is the blood vessel that connects the inferior mesenteric artery with the superior mesenteric artery. The marginal artery runs parallel to the colon for its entire length, providing the blood supply to the colon. Detecting the marginal artery may benefit computer-aided detection (CAD) of colonic polyp. It can be used to identify teniae coli based on their anatomic spatial relationship. It can also serve as an alternative marker for colon localization, in case of colon collapse and inability to directly compute the endoluminal centerline. This paper proposes an automatic method for marginal artery detection on CTC. To the best of our knowledge, this is the first work presented for this purpose. Our method includes two stages. The first stage extracts the blood vessels in the abdominal region. The eigenvalue of Hessian matrix is used to detect line-like structures in the images. The second stage is to reduce the false positives in the first step. We used two different masks to exclude the false positive vessel regions. One is a dilated colon mask which is obtained by colon segmentation. The other is an eroded visceral fat mask which is obtained by fat segmentation in the abdominal region. We tested our method on a CTC dataset with 6 cases. Using ratio-of-overlap with manual labeling of the marginal artery as the standard-of-reference, our method yielded true positive, false positive and false negative fractions of 89%, 33%, 11%, respectively.
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Automated teniae coli detection and identification on Computed Tomographic Colonography
Medical physics, 2012Co-Authors: Zhuoshi Wei, Shijun Wang, Jiamin Liu, Jianhua Yao, Ronald M SummersAbstract:Purpose : Computed Tomographic Colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. Teniae coli are three bands of longitudinal smooth muscle on the colon surface. Teniae coli are important anatomically meaningful landmarks on human colon. In this paper, the authors propose an automatic teniae coli detection method for CT Colonography. Methods : The original CTC slices are first segmented and reconstructed to a 3D colon surface. Then, the 3D colon surface is unfolded using a reversible projection technique. After that the unfolded colon is projected to a 2D height map. The teniae coli are detected using the height map and then reversely projected back to the 3D colon. Since teniae are located at the junctions where the haustral folds meet, the authors apply 2D Gabor filter banks to extract features of haustral folds. The maximum response of the filter banks is then selected as the feature image. The fold centers are then identified based on local maxima and thresholding on the feature image. Connecting the fold centers yields a path of the folds. Teniae coli are extracted as lines running between the fold paths. The authors used the spatial relationship between ileocecal valve (ICV) and teniae mesocolica (TM) to identify the TM, then the teniae omentalis (TO) and the teniae libera (TL) can be identified subsequently. Results : The authors tested the proposed method on 47 cases of 37 patients, 10 of the patients with both supine and prone CT scans. The proposed method yielded performance with an average normalized root mean square error (RMSE) ( ± standard deviation [95% confidence interval]) of 4.87% ( ± 2.93%, [4.05% 5.69%]). Conclusions : The proposed fully-automated teniae coli detection and identification method is accurate and promising for future clinical applications.
Roberto Passariello - One of the best experts on this subject based on the ideXlab platform.
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Computed Tomographic Colonography virtual colonoscopy blinded prospective comparison with conventional colonoscopy for the detection of colorectal neoplasia
Endoscopy, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Valeria Panebianco, Roberto PassarielloAbstract:BACKGROUND AND STUDY AIMS: Computed Tomographic Colonography (CTC), also known as virtual colonoscopy, is a recently introduced imaging modality for the detection of colorectal neoplasia. The aim of our study was to evaluate the performance of CTC in a blinded comparison with conventional colonoscopy. PATIENTS AND METHODS: A total of 66 consecutive, symptomatic patients underwent spiral Computed tomography (CT) examination after standard bowel preparation. CT images were analyzed and subsequently compared with conventional colonoscopy findings. RESULTS: Conventional colonoscopy detected 15 colorectal carcinomas and 52 polyps. CTC correctly identified all carcinomas, 13 of 14 polyps greater than 10.0 mm (sensitivity 92.8 %; 95 % confidence interval (95 % CI); 77 - 100), 11 of 13 polyps between 6.0 and 9.0 mm (sensitivity 84.6 %; 95 % CI; 62 - 100), and six of 25 polyps smaller than 5.0 mm (sensitivity 24 %; 95 % CI; 6 - 42). The per-patient sensitivity and specificity were 93.7 % and 94.1 %, respectively. CONCLUSIONS: Computed Tomographic Colonography is an accurate imaging modality for the detection of colorectal neoplasia, especially for lesions larger than 6.0 mm in diameter.
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Detection of colorectal lesions with virtual Computed Tomographic Colonography.
American Journal of Surgery, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Roberto PassarielloAbstract:Abstract Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter.
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Scientific paper Detection of colorectal lesions with virtual Computed Tomographic Colonography
2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Alberto Schillaci, Roberto PassarielloAbstract:Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter. © 2002 Excerpta Medica, Inc. All rights reserved.
Geoffrey M Forbes - One of the best experts on this subject based on the ideXlab platform.
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Computed Tomographic Colonography: prevalence, nature, and clinical significance of extracolonic findings in a community screening program.
The American journal of gastroenterology, 2005Co-Authors: Marcus W Chin, John T. Edwards, Noellene M. Foster, Richard M Mendelson, Geoffrey M ForbesAbstract:Computed Tomographic Colonography: Prevalence, Nature, and Clinical Significance of Extracolonic Findings in a Community Screening Program
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Randomized single blind trial of two low-volume bowel preparations for screening Computed Tomographic Colonography.
Abdominal imaging, 2004Co-Authors: Geoffrey M Forbes, John T. Edwards, Noellene M. Foster, Christopher J. Wood, Richard M MendelsonAbstract:Background Bowel preparation is an important part of Computed Tomographic Colonography (CTC); we evaluated two small-volume preparations for screening CTC with regard to quality of preparation and patient acceptability.
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Community-based screening by colonoscopy or Computed Tomographic Colonography in asymptomatic average-risk subjects.
The American journal of gastroenterology, 2004Co-Authors: Rosie G Scott, John T. Edwards, Lin Fritschi, Noellene M. Foster, Richard M Mendelson, Geoffrey M ForbesAbstract:Community-Based Screening by Colonoscopy or Computed Tomographic Colonography in Asymptomatic Average-Risk Subjects
Andrea Laghi - One of the best experts on this subject based on the ideXlab platform.
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Computed Tomographic Colonography without cathartic preparation for the detection of colorectal polyps.
Gastroenterology, 2004Co-Authors: Riccardo Iannaccone, Andrea Laghi, Carlo Catalano, Alberto Schillaci, Filippo Mangiapane, Antonietta Lamazza, Giovanni Sinibaldi, Takamichi Murakami, Paolo Sammartino, Masatoshi HoriAbstract:Background & Aims: We prospectively compared the performance of low-dose multidetector Computed Tomographic Colonography (CTC) without cathartic preparation with that of colonoscopy for the detection of colorectal polyps. Methods: A total of 203 patients underwent low-dose CTC without cathartic preparation followed by colonoscopy. Before CTC, fecal tagging was achieved by adding diatrizoate meglumine and diatrizoate sodium to regular meals. No subtraction of tagged feces was performed. Colonoscopy was performed 3–7 days after CTC. Three readers interpreted the CTC examinations separately and independently using a primary 2-dimensional approach using multiplanar reconstructions and 3-dimensional images for further characterization. Colonoscopy with segmental unblinding was used as reference standard. The sensitivity of CTC was calculated both on a per-polyp and a per-patient basis. For the latter, specificity, positive predictive values, and negative predictive values were also calculated. Results: CTC had an average sensitivity of 95.5% (95% confidence interval [CI], 92.1%–99%) for the identification of colorectal polyps ≥8 mm. With regard to per-patient analysis, CTC yielded an average sensitivity of 89.9% (95% CI, 86%–93.7%), an average specificity of 92.2% (95% CI, 89.5%–94.9%), an average positive predictive value of 88% (95% CI, 83.3%–91.5%), and an average negative predictive value of 93.5% (95% CI, 90.9%–96%). Interobserver agreement was high on a per-polyp basis (κ statistic range, .61–.74) and high to excellent on a per-patient basis (κ statistic range, .79–.91). Conclusions: Low-dose multidetector CTC without cathartic preparation compares favorably with colonoscopy for the detection of colorectal polyps.
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Computed Tomographic Colonography virtual colonoscopy blinded prospective comparison with conventional colonoscopy for the detection of colorectal neoplasia
Endoscopy, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Valeria Panebianco, Roberto PassarielloAbstract:BACKGROUND AND STUDY AIMS: Computed Tomographic Colonography (CTC), also known as virtual colonoscopy, is a recently introduced imaging modality for the detection of colorectal neoplasia. The aim of our study was to evaluate the performance of CTC in a blinded comparison with conventional colonoscopy. PATIENTS AND METHODS: A total of 66 consecutive, symptomatic patients underwent spiral Computed tomography (CT) examination after standard bowel preparation. CT images were analyzed and subsequently compared with conventional colonoscopy findings. RESULTS: Conventional colonoscopy detected 15 colorectal carcinomas and 52 polyps. CTC correctly identified all carcinomas, 13 of 14 polyps greater than 10.0 mm (sensitivity 92.8 %; 95 % confidence interval (95 % CI); 77 - 100), 11 of 13 polyps between 6.0 and 9.0 mm (sensitivity 84.6 %; 95 % CI; 62 - 100), and six of 25 polyps smaller than 5.0 mm (sensitivity 24 %; 95 % CI; 6 - 42). The per-patient sensitivity and specificity were 93.7 % and 94.1 %, respectively. CONCLUSIONS: Computed Tomographic Colonography is an accurate imaging modality for the detection of colorectal neoplasia, especially for lesions larger than 6.0 mm in diameter.
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Detection of colorectal lesions with virtual Computed Tomographic Colonography.
American Journal of Surgery, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Roberto PassarielloAbstract:Abstract Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter.
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Scientific paper Detection of colorectal lesions with virtual Computed Tomographic Colonography
2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Alberto Schillaci, Roberto PassarielloAbstract:Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter. © 2002 Excerpta Medica, Inc. All rights reserved.
Riccardo Iannaccone - One of the best experts on this subject based on the ideXlab platform.
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Computed Tomographic Colonography without cathartic preparation for the detection of colorectal polyps.
Gastroenterology, 2004Co-Authors: Riccardo Iannaccone, Andrea Laghi, Carlo Catalano, Alberto Schillaci, Filippo Mangiapane, Antonietta Lamazza, Giovanni Sinibaldi, Takamichi Murakami, Paolo Sammartino, Masatoshi HoriAbstract:Background & Aims: We prospectively compared the performance of low-dose multidetector Computed Tomographic Colonography (CTC) without cathartic preparation with that of colonoscopy for the detection of colorectal polyps. Methods: A total of 203 patients underwent low-dose CTC without cathartic preparation followed by colonoscopy. Before CTC, fecal tagging was achieved by adding diatrizoate meglumine and diatrizoate sodium to regular meals. No subtraction of tagged feces was performed. Colonoscopy was performed 3–7 days after CTC. Three readers interpreted the CTC examinations separately and independently using a primary 2-dimensional approach using multiplanar reconstructions and 3-dimensional images for further characterization. Colonoscopy with segmental unblinding was used as reference standard. The sensitivity of CTC was calculated both on a per-polyp and a per-patient basis. For the latter, specificity, positive predictive values, and negative predictive values were also calculated. Results: CTC had an average sensitivity of 95.5% (95% confidence interval [CI], 92.1%–99%) for the identification of colorectal polyps ≥8 mm. With regard to per-patient analysis, CTC yielded an average sensitivity of 89.9% (95% CI, 86%–93.7%), an average specificity of 92.2% (95% CI, 89.5%–94.9%), an average positive predictive value of 88% (95% CI, 83.3%–91.5%), and an average negative predictive value of 93.5% (95% CI, 90.9%–96%). Interobserver agreement was high on a per-polyp basis (κ statistic range, .61–.74) and high to excellent on a per-patient basis (κ statistic range, .79–.91). Conclusions: Low-dose multidetector CTC without cathartic preparation compares favorably with colonoscopy for the detection of colorectal polyps.
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Computed Tomographic Colonography virtual colonoscopy blinded prospective comparison with conventional colonoscopy for the detection of colorectal neoplasia
Endoscopy, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Valeria Panebianco, Roberto PassarielloAbstract:BACKGROUND AND STUDY AIMS: Computed Tomographic Colonography (CTC), also known as virtual colonoscopy, is a recently introduced imaging modality for the detection of colorectal neoplasia. The aim of our study was to evaluate the performance of CTC in a blinded comparison with conventional colonoscopy. PATIENTS AND METHODS: A total of 66 consecutive, symptomatic patients underwent spiral Computed tomography (CT) examination after standard bowel preparation. CT images were analyzed and subsequently compared with conventional colonoscopy findings. RESULTS: Conventional colonoscopy detected 15 colorectal carcinomas and 52 polyps. CTC correctly identified all carcinomas, 13 of 14 polyps greater than 10.0 mm (sensitivity 92.8 %; 95 % confidence interval (95 % CI); 77 - 100), 11 of 13 polyps between 6.0 and 9.0 mm (sensitivity 84.6 %; 95 % CI; 62 - 100), and six of 25 polyps smaller than 5.0 mm (sensitivity 24 %; 95 % CI; 6 - 42). The per-patient sensitivity and specificity were 93.7 % and 94.1 %, respectively. CONCLUSIONS: Computed Tomographic Colonography is an accurate imaging modality for the detection of colorectal neoplasia, especially for lesions larger than 6.0 mm in diameter.
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Detection of colorectal lesions with virtual Computed Tomographic Colonography.
American Journal of Surgery, 2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Emilio Di Giulio, Alberto Schillaci, Roberto PassarielloAbstract:Abstract Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter.
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Scientific paper Detection of colorectal lesions with virtual Computed Tomographic Colonography
2002Co-Authors: Andrea Laghi, Riccardo Iannaccone, Iacopo Carbone, Carlo Catalano, Alberto Schillaci, Roberto PassarielloAbstract:Background: The aim of our study was to compare the performance of virtual Computed Tomographic Colonography with that of conventional colonoscopy in a blinded, prospective study in 165 patients with suspected colorectal lesions. Methods: There were 165 patients, all referred for conventional colonoscopy, who underwent preliminary virtual Computed Tomographic Colonography. Computed tomograhic images of all suspected lesions were analyzed and subsequently compared with conventional colonoscopy findings. Results: There were 30 colorectal cancers and 37 polyps identified at conventional colonoscopy. Virtual Computed Tomographic Colonography correctly detected all cancers, as well as 11 of 12 polyps of 10 mm in diameter or larger (sensitivity, 92%); 14 of 17 polyps between 6 and 9 mm (sensitivity, 82%); and 4 of 8 polyps of 5 mm or smaller (sensitivity, 50%). The per-patient sensitivity and specificity were 92% and 97%, respectively. Conclusions: Virtual Computed Tomographic Colonography has a diagnostic sensitivity similar to that of conventional colonoscopy for the detection of colorectal lesions larger than 6 mm in diameter. © 2002 Excerpta Medica, Inc. All rights reserved.