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Accounting for anatomical noise in search-capable model observers for planar nuclear imaging

Lookup NU author(s): Dr Anando SenORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Model observers intended to predict the diagnostic performance of human observers should account for the effects of both quantum and anatomical noise. We compared the abilities of several visual-search (VS) and scanning Hotelling-type models to account for anatomical noise in a localization receiver operating characteristic (LROC) study involving simulated nuclear medicine images. Our VS observer invoked a two-stage process of search and analysis. The images featured lesions in the prostate and pelvic lymph nodes. Lesion contrast and the geometric resolution and sensitivity of the imaging collimator were the study variables. A set of anthropomorphic mathematical phantoms was imaged with an analytic projector based on eight parallel-hole collimators with different sensitivity and resolution properties. The LROC study was conducted with human observers and the channelized nonprewhitening, channelized Hotelling (CH) and VS model observers. The CH observer was applied in a “background-known-statistically” protocol while the VS observer performed a quasi-background-known-exactly task. Both of these models were applied with and without internal noise in the decision variables. A perceptual search threshold was also tested with the VS observer. The model observers without inefficiencies failed to mimic the average performance trend for the humans. The CH and VS observers with internal noise matched the humans primarily at low collimator sensitivities. With both internal noise and the search threshold, the VS observer attained quantitative agreement with the human observers. Computational efficiency is an important advantage of the VS observer.

Publication metadata

Author(s): Sen A, Gifford HC

Publication type: Article

Publication status: Published

Journal: Journal of Medical Imaging

Year: 2016

Volume: 3

Issue: 1

Online publication date: 26/01/2016

Acceptance date: 23/12/2015

Date deposited: 18/03/2022

ISSN (print): 2329-4302

ISSN (electronic): 2329-4310

Publisher: SPIE


DOI: 10.1117/1.JMI.3.1.015502


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