Nodule detection in two-component noise: toward patient structure

Arthur E. Burgess; Xing Li; Craig K. Abbey

doi:10.1117/12.271279

16 April 1997 Nodule detection in two-component noise: toward patient structure

Arthur E. Burgess, Xing Li, Craig K. Abbey

Proceedings Volume 3036, Medical Imaging 1997: Image Perception; (1997) https://doi.org/10.1117/12.271279
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

Abstract

It is common, in discussions of lesion (signal) detection in radiology, to refer to patient anatomy as structured noise. This is, of course, a gross over-simplification -- because it does not take issues of phase coherence/incoherence into account. However, there are benefits from investigating phenomenological issues of signal detection in two component noise -- with one component being broad band (white) noise designed to simulate image noise and the other (background) component filtered to match the power spectrum of some aspect of imaged patient anatomy. The purpose of the experiments described in this paper is to develop an understanding of how the power spectrum of simulated patient structure affects detectability of simulated lesions. We report results of a number of investigations of human and model observer performance. Example tasks are: detection of simulated lung nodules in noise filtered to simulate background lumpy structure at a variety of scales, detection of nodules in fractal-like power law noise, and detection of simulated microcalcification clusters and simulated breast mass lesions in power law noise designed to simulate mammographic parenchymal structure. Human results are compared to three observer models and are fitted very well by a channelized Fisher-Hotelling model. The nonprewhitening model with eye filter does not agree with human results over much of the parameter ranges.

Citation Download Citation

Arthur E. Burgess, Xing Li, and Craig K. Abbey "Nodule detection in two-component noise: toward patient structure", Proc. SPIE 3036, Medical Imaging 1997: Image Perception, (16 April 1997); https://doi.org/10.1117/12.271279

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