Methods of estimation-based segmentation and transmission-less attenuation and scatter compensation in nuclear medicine imaging
AssigneeWashington University
InventorsAbhinav Kumar Jha, Ziping Liu, Hae Sol Moon, Zitong Yu, Md Ashequr Rahman
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Abstract
Among the various aspects of the present disclosure is the provision of methods for estimation-based segmentation of nuclear medicine images, as well as methods of transmission-less attenuation and scatter compensation of nuclear medicine images.
Claims10
A computer-implemented method for segmenting a nuclear medicine image, the method comprising transforming, using a computing device, a nuclear medicine image dataset into a segmented nuclear medicine image dataset using a deep learning network, wherein the segmented nuclear medicine image dataset comprises a plurality of voxels, each voxel associated with at least one voxel volume fraction, each voxel volume fraction indicative of a fraction classified as one tissue type within each voxel.
A computer-implemented method for performing transmission-less attenuation and scatter compensation (ASC) on a nuclear medicine image, the method comprising:
- a. reconstructing, using a computing device, a scatter window dataset corresponding to the nuclear medicine image to obtain a preliminary attenuation map;
- b. transforming, using the computing device, the preliminary attenuation map to a final estimated attenuation map by segmenting the preliminary attenuation map using a deep learning network;
- and
- c. reconstructing, using the computing device, the nuclear medicine image based on a photopeak window associated with the nuclear medicine image in combination with the final estimated attenuation map.
Dependencies are inferred from the claim text.