Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images

Minah Han; Jongduk Baek

doi:10.1117/12.2534003

Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images

Minah Han, Jongduk Baek

School of Integrated Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We predict human observer performance for lesion detection on breast cone beam computed tomography (CBCT) images using single-slice and multislice model observers with a constant internal noise level. We evaluate human observer performance on single-slice and multislice simulated breast CBCT images with 1 mm signal, and predict the performance using model observers. We use a channelized Hotelling observer (CHO) and nonprewhitening observer with eye-filter (NPWE). We employ dense difference-of-Gaussian (D-DOG) channels for CHO, and eyefilter with peak value at 7 cyc/deg for NPWE. We include channel internal noise for CHO and decision variable internal noise for NPWE. For single-slice images, D-DOG CHO and NPWE predict human observer performance well. For multislice images, D-DOG CHO overestimates human observer performance, while NPWE predict human observer performance successfully.

Original language	English
Title of host publication	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Editors	Samuel Matej, Scott D. Metzler
Publisher	SPIE
ISBN (Electronic)	9781510628373
DOIs	https://doi.org/10.1117/12.2534003
Publication status	Published - 2019
Event	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 - Philadelphia, United States Duration: 2019 Jun 2 → 2019 Jun 6

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11072
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019
Country/Territory	United States
City	Philadelphia
Period	19/6/2 → 19/6/6

Bibliographical note

Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2534003

Cite this

Han, M., & Baek, J. (2019). Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images. In S. Matej, & S. D. Metzler (Eds.), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine Article 110721P (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072). SPIE. https://doi.org/10.1117/12.2534003

Han, Minah ; Baek, Jongduk. / Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images. 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. editor / Samuel Matej ; Scott D. Metzler. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).

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title = "Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images",

abstract = "We predict human observer performance for lesion detection on breast cone beam computed tomography (CBCT) images using single-slice and multislice model observers with a constant internal noise level. We evaluate human observer performance on single-slice and multislice simulated breast CBCT images with 1 mm signal, and predict the performance using model observers. We use a channelized Hotelling observer (CHO) and nonprewhitening observer with eye-filter (NPWE). We employ dense difference-of-Gaussian (D-DOG) channels for CHO, and eyefilter with peak value at 7 cyc/deg for NPWE. We include channel internal noise for CHO and decision variable internal noise for NPWE. For single-slice images, D-DOG CHO and NPWE predict human observer performance well. For multislice images, D-DOG CHO overestimates human observer performance, while NPWE predict human observer performance successfully.",

author = "Minah Han and Jongduk Baek",

note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 ; Conference date: 02-06-2019 Through 06-06-2019",

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language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

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Han, M & Baek, J 2019, Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images. in S Matej & SD Metzler (eds), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine., 110721P, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11072, SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019, Philadelphia, United States, 19/6/2. https://doi.org/10.1117/12.2534003

Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images. / Han, Minah; Baek, Jongduk.
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. ed. / Samuel Matej; Scott D. Metzler. SPIE, 2019. 110721P (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Baek, Jongduk

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N2 - We predict human observer performance for lesion detection on breast cone beam computed tomography (CBCT) images using single-slice and multislice model observers with a constant internal noise level. We evaluate human observer performance on single-slice and multislice simulated breast CBCT images with 1 mm signal, and predict the performance using model observers. We use a channelized Hotelling observer (CHO) and nonprewhitening observer with eye-filter (NPWE). We employ dense difference-of-Gaussian (D-DOG) channels for CHO, and eyefilter with peak value at 7 cyc/deg for NPWE. We include channel internal noise for CHO and decision variable internal noise for NPWE. For single-slice images, D-DOG CHO and NPWE predict human observer performance well. For multislice images, D-DOG CHO overestimates human observer performance, while NPWE predict human observer performance successfully.

AB - We predict human observer performance for lesion detection on breast cone beam computed tomography (CBCT) images using single-slice and multislice model observers with a constant internal noise level. We evaluate human observer performance on single-slice and multislice simulated breast CBCT images with 1 mm signal, and predict the performance using model observers. We use a channelized Hotelling observer (CHO) and nonprewhitening observer with eye-filter (NPWE). We employ dense difference-of-Gaussian (D-DOG) channels for CHO, and eyefilter with peak value at 7 cyc/deg for NPWE. We include channel internal noise for CHO and decision variable internal noise for NPWE. For single-slice images, D-DOG CHO and NPWE predict human observer performance well. For multislice images, D-DOG CHO overestimates human observer performance, while NPWE predict human observer performance successfully.

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Han M, Baek J. Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images. In Matej S, Metzler SD, editors, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. SPIE. 2019. 110721P. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2534003

Multislice anthropomorphic model observer for detectability evaluation on breast cone beam CT images

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