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Grant Details

Grant Number: 5R01EB018958-04 Interpret this number
Primary Investigator: Eckstein, Miguel
Organization: University Of California Santa Barbara
Project Title: Assessment of Medical Image Quality with Foveated Search Models
Fiscal Year: 2018


Abstract

 DESCRIPTION (provided by applicant): Medical image quality can be objectively defined in terms of diagnostic decision accuracy in clinically relevant perceptual tasks. Because of the high cost and effort involved in evaluating image quality using clinical studies, especially in early technological developments, there has been an ongoing effort to develop numerical algorithms (model observers) that can be applied to images to predict human accuracy in clinically relevant perceptual tasks. In recent years model observers have transitioned from laboratory investigations to actual tools used in technology development in the industry and for image quality evaluation by manufacturers to seek approval from the Food and Drug Administration. However, the recent increase of the use of 3D medical images (computed tomography, breast tomosynthesis, magnetic resonance) has motivated a need for the development of the next generation of model observers. A fundamental limitation of current model observers is that they disregard that the human brain processes an image with decreasing spatial resolution from the point of fixation. With 3D data-sets, radiologists rarely exhaustively fixate every region of every slice; instead, they process a significant portion of images with their retinal periphery which has drastically different visual processing. Increased computer power and recent advances in the understanding of the computational neuroscience of visual search provide the opportunity to develop the next generation model observers which potentially can more accurately characterize how radiologists scrutinize medical images, as well as their decision accuracy and errors. The current project proposes to develop the 1st model observer to emulate radiologists by processing medical images with varying spatial processing resolution across the human visual field, searching through the image with simulated eye movements, and reaching a decision through integration across fixations. The foveated search model, which makes eye movements unlike any previous model observer in medical imaging, will be the 1st model to emulate radiologists in making two distinct types of errors: search errors ( missed lesions that are not fixated) perceptual errors (missed lesion that are fixated). The decisions and eye movements of over twenty radiologists reading digital breast tomosynthesis (DBT) images will be compared to the newly proposed foveated search model and a comprehensive list of existing non-scanning and scanning model observers in what will represent the most extensive validation study to date of model observers with actual radiologists' decisions. The newly proposed model will be utilized to optimize DBT acquisition geometry and compared to use of current metrics of medical image quality. If successful, the newly proposed foveated search model will allow for more accuracy assessment of medical image quality, could be utilized to accelerate the evaluation of new technology, optimize parameters of current technology and gain a better understanding how radiologists search and reach diagnostic decisions.



Publications

Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets.
Authors: Lago M.A. , Jonnalagadda A. , Abbey C.K. , Barufaldi B.B. , Bakic P.R. , Maidment A.D.A. , Leung W.K. , Weinstein S.P. , Englander B.S. , Eckstein M.P. .
Source: Current biology : CB, 2021-03-08; 31(5), p. 1099-1106.e5.
EPub date: 2021-01-19.
PMID: 33472051
Related Citations

Foveated Model Observers for Visual Search in 3D Medical Images.
Authors: Lago M.A. , Abbey C.K. , Eckstein M.P. .
Source: IEEE transactions on medical imaging, 2021 Mar; 40(3), p. 1021-1031.
EPub date: 2021-03-02.
PMID: 33315556
Related Citations

Measurement of the useful field of view for single slices of different imaging modalities and targets.
Authors: Lago M.A. , Sechopoulos I. , Bochud F.O. , Eckstein M.P. .
Source: Journal of medical imaging (Bellingham, Wash.), 2020 Mar; 7(2), p. 022411.
EPub date: 2020-02-08.
PMID: 32064303
Related Citations

Human observer templates for lesion discrimination tasks.
Authors: Abbey C.K. , Samuelson F.W. , Zeng R. , Boone J.M. , Eckstein M.P. , Myers K.J. .
Source: Proceedings of SPIE--the International Society for Optical Engineering, 2020 Feb; 11316, .
EPub date: 2020-03-16.
PMID: 33384465
Related Citations

Benefits of Independent Double Reading in Digital Mammography: A Theoretical Evaluation of All Possible Pairing Methodologies.
Authors: Brennan P.C. , Ganesan A. , Eckstein M.P. , Ekpo E.U. , Tapia K. , Mello-Thoms C. , Lewis S. , Juni M.Z. .
Source: Academic radiology, 2019 06; 26(6), p. 717-723.
EPub date: 2018-07-29.
PMID: 30064917
Related Citations

Evaluation of non-Gaussian statistical properties in virtual breast phantoms.
Authors: Abbey C.K. , Bakic P.R. , Pokrajac D.D. , Maidment A.D.A. , Eckstein M.P. , Boone J.M. .
Source: Journal of medical imaging (Bellingham, Wash.), 2019 Apr; 6(2), p. 025502.
EPub date: 2019-06-14.
PMID: 31259201
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Introduction to Special Issue on Perceptual Learning.
Authors: Eckstein M.P. , Yu C. , Sagi D. , Carrasco M. , Lu Z.L. .
Source: Vision research, 2018 11; 152, p. 1-2.
PMID: 30522730
Related Citations

Classification images for localization performance in ramp-spectrum noise.
Authors: Abbey C.K. , Samuelson F.W. , Zeng R. , Boone J.M. , Eckstein M.P. , Myers K. .
Source: Medical physics, 2018 May; 45(5), p. 1970-1984.
EPub date: 2018-04-11.
PMID: 29532479
Related Citations

Interactions of lesion detectability and size across single-slice DBT and 3D DBT.
Authors: Lago M.A. , Abbey C.K. , Barufaldi B. , Bakic P.R. , Weinstein S.P. , Maidment A.D. , Eckstein M.P. .
Source: Proceedings of SPIE--the International Society for Optical Engineering, 2018 Feb; 10577, .
EPub date: 2018-03-07.
PMID: 32435080
Related Citations

Evaluation of Search Strategies for Microcalcifications and Masses in 3D Images.
Authors: Eckstein M.P. , Lago M.A. , Abbey C.K. .
Source: Proceedings of SPIE--the International Society for Optical Engineering, 2018 Feb; 10577, .
EPub date: 2018-03-07.
PMID: 32435079
Related Citations

Object detection through search with a foveated visual system.
Authors: Akbas E. , Eckstein M.P. .
Source: PLoS computational biology, 2017 Oct; 13(10), p. e1005743.
EPub date: 2017-10-09.
PMID: 28991906
Related Citations

The wisdom of crowds for visual search.
Authors: Juni M.Z. , Eckstein M.P. .
Source: Proceedings of the National Academy of Sciences of the United States of America, 2017-05-23; 114(21), p. E4306-E4315.
EPub date: 2017-05-10.
PMID: 28490500
Related Citations

Foveated Model Observers to predict human performance in 3D images.
Authors: Lago M.A. , Abbey C.K. , Eckstein M.P. .
Source: Proceedings of SPIE--the International Society for Optical Engineering, 2017-02-11; 10136, .
EPub date: 2017-03-10.
PMID: 29176921
Related Citations

The role of extra-foveal processing in 3D imaging.
Authors: Eckstein M.P. , Lago M.A. , Abbey C.K. .
Source: Proceedings of SPIE--the International Society for Optical Engineering, 2017-02-11; 10136, .
EPub date: 2017-03-10.
PMID: 29176920
Related Citations

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography.
Authors: Ba A. , Eckstein M.P. , Racine D. , Ott J.G. , Verdun F. , Kobbe-Schmidt S. , Bochud F.O. .
Source: Journal of medical imaging (Bellingham, Wash.), 2016 Jan; 3(1), p. 011009.
EPub date: 2015-12-29.
PMID: 26719849
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