University of Massachusetts Medical School Faculty Publications

Title

A Multiclass Model Observer for Multislice-Multiview Images

UMMS Affiliation

Department of Radiology

Publication Date

2006-10-29

Document Type

Conference Proceeding

Disciplines

Analytical, Diagnostic and Therapeutic Techniques and Equipment | Bioimaging and Biomedical Optics | Biological and Chemical Physics | Nuclear | Nuclear Engineering | Radiology

Abstract

A human-model observer for tumor detection-localization studies featuring multislice-multiview (or volumetric) image displays has been introduced. This volumetric observer, an extension of multiclass linear observers previously tested with single-slice and multislice displays, produces rating and localization data by integrating perception measurements from the different image views. A channelized NPW (CNPW) version of the observer was evaluated against humans for a background-known-exactly (BKE) detection task involving localization of Tc-99m Neotect lesions in simulated SPECT lung images. An LROC study evaluated two RBI reconstruction strategies that used different combinations of corrections for attenuation, scatter, and distance-dependent system resolution, and coronal, sagittal, and transverse slices were presented to the observers. Model-observer ranking of these strategies did not match that of the humans. Follow-up studies exploring several possible remedies for the model observer, including strategy-specific search regions and an internal-noise mechanism, showed little change. Future work will examine variations from the BKE assumption as a means of reconciling the rankings.

Keywords

Displays, Humans, Neoplasms, Testing, Volume measurement, Lesions, Lungs, Image reconstruction, Attenuation, Scattering

DOI of Published Version

10.1109/NSSMIC.2006.354223

Source

Gifford HC, Lehovich A, King MA. A Multiclass Model Observer for Multislice-Multiview Images. IEEE Nucl Sci Symp Conf Rec (1997). 2006;3:1687-1691. doi: 10.1109/NSSMIC.2006.354223. PMID: 19194524; PMCID: PMC2633942. Link to article on publisher's site

Related Resources

Link to Article in PubMed

Journal/Book/Conference Title

IEEE Nuclear Science Symposium conference record. Nuclear Science Symposium

PubMed ID

19194524

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