A stereo matching model observer for stereoscopic viewing of 3D medical images

Gezheng Wen; Mia K. Markey; Gautam S. Muralidlhar

doi:10.1117/12.2043175

11 March 2014 A stereo matching model observer for stereoscopic viewing of 3D medical images

Gezheng Wen, Mia K. Markey, Gautam S. Muralidlhar

Author Affiliations +

Proceedings Volume 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment; 90370Z (2014) https://doi.org/10.1117/12.2043175
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Stereoscopic viewing of 3D medical imaging data has the potential to increase the detection of abnormalities. We present a new stereo model observer inspired by the characteristics of stereopsis in human vision. Given a stereo pair of images of an object (i.e., left and right images separated by a small displacement), the model observer rst nds the corresponding points between the two views, and then fuses them together to create a 2D cyclopean view. Assuming that the cyclopean view has extracted most of the 3D information presented in the stereo pair, a channelized Hotelling observer (CHO) can be utilized to make decisions. We conduct a simulation study that attempts to mimic the detection of breast lesions on stereoscopic viewing of breast tomosynthesis projection images. We render voxel datasets that contain random 3D power-law noise to model normal breast tissues with various breast densities. 3D Gaussian signal is added to some of the datasets to model the presence of a breast lesion. By changing the separation angle between the two views, multiple stereo pairs of projection images are generated for each voxel dataset. The performance of the model is evaluated in terms of the accuracy of binary decisions on the presence of the simulated lesions.

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Gezheng Wen, Gezheng Wen, Mia K. Markey, Mia K. Markey, Gautam S. Muralidlhar, Gautam S. Muralidlhar, "A stereo matching model observer for stereoscopic viewing of 3D medical images", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370Z (11 March 2014); doi: 10.1117/12.2043175; https://doi.org/10.1117/12.2043175

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