Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front.
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| Title: | Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front. |
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| Authors: | Jiang Li1, Huang, Adam2, Yao, Jack2, Jiamin Liu2, Van Uitert, Robert L.2, Petrick, Nicholas3, Summers, Ronald M.2 |
| Source: | Medical Physics. Jan2009, Vol. 36 Issue 1, p201-212. 12p. 1 Black and White Photograph, 1 Diagram, 3 Charts, 3 Graphs. |
| Subjects: | Algorithms, Polyps, Colon (Anatomy), Pareto principle, Radiology |
| Abstract: | A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for detecting polyps sized 10 mm or larger in diameter. However, many medium-sized polyps, 6–9 mm in diameter, were missed in the initial detection procedure. In this paper, the task of finding optimal thresholds as a multiobjective optimization problem was formulated, and a genetic algorithm to solve it was utilized by evolving the Pareto front of the Pareto optimal set. The new CTC CAD system was tested on 792 patients. The sensitivities of the optimized system improved significantly, from 61.68% to 74.71% with an increase of 13.03% (95% CI [6.57%, 19.5%], p=7.78×10-5) for the size category of 6–9 mm polyps, from 65.02% to 77.4% with an increase of 12.38% (95% CI [6.23%, 18.53%], p=7.95×10-5) for polyps 6 mm or larger, and from 82.2% to 90.58% with an increase of 8.38% (95%CI [0.75%, 16%], p=0.03) for polyps 8 mm or larger at comparable false positive rates. The sensitivities of the optimized system are nearly equivalent to those of expert radiologists. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 35982779 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Jiang+Li%22">Jiang Li</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Huang%2C+Adam%22">Huang, Adam</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Yao%2C+Jack%22">Yao, Jack</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Jiamin+Liu%22">Jiamin Liu</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Van+Uitert%2C+Robert+L%2E%22">Van Uitert, Robert L.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Petrick%2C+Nicholas%22">Petrick, Nicholas</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Summers%2C+Ronald+M%2E%22">Summers, Ronald M.</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Physics%22">Medical Physics</searchLink>. Jan2009, Vol. 36 Issue 1, p201-212. 12p. 1 Black and White Photograph, 1 Diagram, 3 Charts, 3 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Polyps%22">Polyps</searchLink><br /><searchLink fieldCode="DE" term="%22Colon+%28Anatomy%29%22">Colon (Anatomy)</searchLink><br /><searchLink fieldCode="DE" term="%22Pareto+principle%22">Pareto principle</searchLink><br /><searchLink fieldCode="DE" term="%22Radiology%22">Radiology</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for detecting polyps sized 10 mm or larger in diameter. However, many medium-sized polyps, 6–9 mm in diameter, were missed in the initial detection procedure. In this paper, the task of finding optimal thresholds as a multiobjective optimization problem was formulated, and a genetic algorithm to solve it was utilized by evolving the Pareto front of the Pareto optimal set. The new CTC CAD system was tested on 792 patients. The sensitivities of the optimized system improved significantly, from 61.68% to 74.71% with an increase of 13.03% (95% CI [6.57%, 19.5%], p=7.78×10-5) for the size category of 6–9 mm polyps, from 65.02% to 77.4% with an increase of 12.38% (95% CI [6.23%, 18.53%], p=7.95×10-5) for polyps 6 mm or larger, and from 82.2% to 90.58% with an increase of 8.38% (95%CI [0.75%, 16%], p=0.03) for polyps 8 mm or larger at comparable false positive rates. The sensitivities of the optimized system are nearly equivalent to those of expert radiologists. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1118/1.3040177 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 201 Subjects: – SubjectFull: Algorithms Type: general – SubjectFull: Polyps Type: general – SubjectFull: Colon (Anatomy) Type: general – SubjectFull: Pareto principle Type: general – SubjectFull: Radiology Type: general Titles: – TitleFull: Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jiang Li – PersonEntity: Name: NameFull: Huang, Adam – PersonEntity: Name: NameFull: Yao, Jack – PersonEntity: Name: NameFull: Jiamin Liu – PersonEntity: Name: NameFull: Van Uitert, Robert L. – PersonEntity: Name: NameFull: Petrick, Nicholas – PersonEntity: Name: NameFull: Summers, Ronald M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 00942405 Numbering: – Type: volume Value: 36 – Type: issue Value: 1 Titles: – TitleFull: Medical Physics Type: main |
| ResultId | 1 |
