Towards reduced-preparation spectral-CT-colonography utilizing local covariance

Rafael Wiemker, Tobias Klinder, Jörg Sabczynski, Amar Dhanantwari, Chansik An, Benjamin M. Yeh, Judy Yee

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

Abstract

In CT colonography (CTC), residual stool is a possible confounder in the detection of colonic polyps. While there is a clear clinical need for reduced or minimal bowel preparation for CT colonography, residual stool that is poorly tagged by oral contrast agent prevents satisfactory electronic cleansing (EC) by standard methods on conventional CT. Our study aims to answer quantitatively whether dual-layer spectral-CT allows superior discrimination of residual stool. 60 spectral CT colonography scans were obtained in clinical practice, and careful exhaustive ground truth was established by consensus reading. Results indicate that spectral CT adds significant discrimination power, in particular when utilizing local spectral variances and covariances, which can be computed efficiently by standard Gaussian filter operations. Simple linear spectral material separation, however, is sufficient only in extended homogeneous regions. In subtle finely structured transition areas, non-linear classifiers or convolutional neural networks are required because of non-linear local multi-material superposition effects.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2020
Subtitle of host publicationImage Processing
EditorsIvana Isgum, Bennett A. Landman
PublisherSPIE
ISBN (Electronic)9781510633933
DOIs
StatePublished - 2020
EventMedical Imaging 2020: Image Processing - Houston, United States
Duration: Feb 17 2020Feb 20 2020

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11313
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2020: Image Processing
CountryUnited States
CityHouston
Period2/17/202/20/20

Keywords

  • Colon cancer screening
  • CT colonoscopy
  • Spectral CT
  • Spectral material classification

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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