Paper
16 April 1997 Comparison of the channelized Hotelling and human observers for lesion detection in hepatic SPECT imaging
Michael A. King, Daniel J. de Vries, Edward J. Soares
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Abstract
The relative rankings of the channelized Hotelling model observer were compared to those of the human observers for the task of detecting 'hot' tumors in simulated hepatic SPECT slices. The signal-to-noise ratios (SNRs) were determined using eighty images for each of three slice locations. The acquisition and processing strategies investigated were: (1) imaging solely primary photons, (2) imaging primary plus scatter within a 20% symmetric energy window for Tc-99m, (3) imaging with primary plus an elevated amount of scatter, (4) energy-spectrum-based scatter compensation of the primary plus scatter acquisitions, and (5) energy-spectrum-based scatter compensation of the acquisitions with an elevated amount of scatter. Both square non-overlapping channels (SQR), and overlapping difference- of-Gaussian channels (DOG) were incorporated into the Hotelling model observer. When the scatter compensation results were excluded, both channelized Hotelling model observers exhibited a strong correlation with the rankings of the human-observers. With the inclusion of the scatter compensation results, only with the DOG model observer was the null-hypothesis of no correlation rejected at the p equals 0.05 level. It is concluded that further investigation of the channel model used with the Hotelling observer is indicated to determine if better correlation can be obtained.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael A. King, Daniel J. de Vries, and Edward J. Soares "Comparison of the channelized Hotelling and human observers for lesion detection in hepatic SPECT imaging", Proc. SPIE 3036, Medical Imaging 1997: Image Perception, (16 April 1997); https://doi.org/10.1117/12.271290
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Cited by 20 scholarly publications.
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KEYWORDS
Tumors

Signal to noise ratio

Single photon emission computed tomography

Liver

Monte Carlo methods

Photons

Statistical modeling

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