Literature DB >> 17021701

Computer assisted detection software for CT colonography: effect of sphericity filter on performance characteristics for patients with and without fecal tagging.

Jamshid Dehmeshki1, Steve Halligan, Stuart A Taylor, Mary E Roddie, Justine McQuillan, Lesley Honeyfield, Hamdan Amin.   

Abstract

The aim of this study is to investigate the effect of changing sphericity filter values on performance of a computer assisted detection (CAD) system for CT colonography for data with and without fecal tagging. Colonography data from 138 patients with 317 validated polyps were divided into those with (86) and without (52) fecal tagging. Polyp coordinates were established by three observers and datasets analysed subsequently by a proprietary CAD system used at four discrete sphericity filter settings. Prompts were compared with the known coordinates in order to determine sensitivity and specificity. Sensitivity was highest at low sphericity; of 164 polyps 6 mm or more, 144 (87.8%) were detected at sphericity 0.3, and 132 (80.1%) at sphericity 0.9. Of 42 polyps measuring 10 mm or more, 40 (95.2%) were detected at sphericity 0.3, and 36 (85.7%) at sphericity 0.9. There was no significant difference in sensitivity for tagged and un-tagged data but specificity was reduced in tagged data at low sphericity and significantly reduced in untagged data at high sphericity. CAD had a sensitivity of 95.2% for polyps measuring 1 cm or more and 87.8% for polyps 6 mm or more when used at a sphericity setting of 0.3. Higher sphericity settings increased specificity while reducing sensitivity. The bowel preparation used significantly impacts on specificity.

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Year:  2006        PMID: 17021701     DOI: 10.1007/s00330-006-0430-z

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  20 in total

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Authors:  S A Taylor; S Halligan; V Goh; S Morley; W Atkin; C I Bartram
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Authors:  C Daniel Johnson; Alicia Y Toledano; Benjamin A Herman; Abraham H Dachman; Elizabeth G McFarland; Matthew A Barish; James A Brink; Randy D Ernst; Joel G Fletcher; Robert A Halvorsen; Amy K Hara; Kenneth D Hopper; Robert E Koehler; David S k Lu; Michael Macari; Robert L Maccarty; Frank H Miller; Martina Morrin; Erik K Paulson; Judy Yee; Michael Zalis
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Review 2.  Progress in Fully Automated Abdominal CT Interpretation.

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4.  Comparative performance of a primary-reader and second-reader paradigm of computer-aided detection for CT colonography in a low-prevalence screening population.

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5.  CT colonography: computer-aided detection of morphologically flat T1 colonic carcinoma.

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  5 in total

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