Automatic strategy for CHO channel reduction in x-ray angiography systems

Daniel Gomez-Cardona, Shuai Leng, Christopher P. Favazza, Beth Ann Schueler, Kenneth A. Fetterly

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

Abstract

Multiple efforts have been made in x-ray angiography to transition from traditional image quality metrics to mathematical observer models. Recent works have successfully implemented the channelized Hotelling observer (CHO) model for x-ray angiography systems. However, in these works the channel selection process is ambiguous and limits to identifying a range of frequencies and other channel parameters that are believed to represent the most relevant features of the imaging tasks. This channel selection rationale can be sufficient for certain simple scenarios but it might not be enough for more complex ones. On the other hand, it has been shown that besides dealing with the well-known bias caused by a finite number of samples, there is also another source of bias in the estimation of the detectability index in x-ray angiography. Such source of bias has been attributed to nonrandom differences in noise between images acquired at different time points, also referred as temporally variable nonstationary noise. This work proposes a task-specific automated method for optimal channel selection and corrects for the influence of bias due to temporally variable nonstationary noise, particular from x-ray angiography systems. The proposed method is computationally inexpensive, provides time efficient selection of optimal channels, and contributes to minimize bias, all of these without significantly compromising the accuracy of the detectability index estimation. This method for channel optimization can be readily adapted to other imaging modalities.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2019
Subtitle of host publicationImage Perception, Observer Performance, and Technology Assessment
EditorsRobert M. Nishikawa, Frank W. Samuelson
PublisherSPIE
ISBN (Electronic)9781510625518
DOIs
StatePublished - Jan 1 2019
EventMedical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment - San Diego, United States
Duration: Feb 20 2019Feb 21 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10952
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
CountryUnited States
CitySan Diego
Period2/20/192/21/19

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Keywords

  • Backward elimination
  • Bias
  • Channel selection
  • CHO
  • Detectability index
  • Observer model
  • X-ray angiography

ASJC Scopus subject areas

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

Cite this

Gomez-Cardona, D., Leng, S., Favazza, C. P., Schueler, B. A., & Fetterly, K. A. (2019). Automatic strategy for CHO channel reduction in x-ray angiography systems. In R. M. Nishikawa, & F. W. Samuelson (Eds.), Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment [1095205] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10952). SPIE. https://doi.org/10.1117/12.2513609