Application of CT acquisition parameters as features in computer-aided detection for CT colonography

Janne J. Näppi, Don Rockey, Daniele Regge, Hiroyuki Yoshida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Studies have indicated that the acquisition parameters of computed tomography (CT) scans can have significant effect on the accuracy of computer-aided detection (CAD) in CT colonography. We investigated whether these parameters can be used as external features with conventional image-based features to improve CAD performance. A CAD scheme was trained with the CT colonography data of 886 patients, and it was tested with an independent set of 705 CT colonography cases. The results indicate that some CT acquisition parameters can be used successfully as features of the detected lesion candidates for improving the detection accuracy of CAD for flat lesions and carcinomas.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages69-77
Number of pages9
Volume7601 LNCS
DOIs
Publication statusPublished - 2012
Event4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France
Duration: Oct 1 2012Oct 1 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7601 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period10/1/1210/1/12

Keywords

  • Computed tomographic colonography
  • computer-aided detection
  • CT acquisition
  • polyp detection
  • virtual colonoscopy

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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