A preliminary investigation of reduced-view image reconstruction from low dose breast CT data

Junguo Bian; Xiao Han; Kai Yang; Emil Y. Sidky; John M Boone; Xiaochuan Pan

doi:10.1117/12.911325

A preliminary investigation of reduced-view image reconstruction from low dose breast CT data

Junguo Bian, Xiao Han, Kai Yang, Emil Y. Sidky, John M Boone, Xiaochuan Pan

Radiology

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

3 Scopus citations

Abstract

Analytic-based algorithms such as the FDK algorithm is used currently for image reconstruction from data acquired with prototypes of dedicated breast CT scanners. In general, analytic-based algorithms require data collected at a large number (∼500) of views. In current breast-CT scans, imaging dose delivered to the patient is about the same as that used in a typical two-view mammography exam. This highly limited total imaging dose, when distributed over a large number of views in breast CT, can result in low-SNR data. There exists a renewed interest in developing optimization-based (i.e., iterative) algorithms for image reconstruction from low-SNR data and/or from sparse-view data collected at a reduced number of views. Results of recent studies on optimization-based algorithms from CT data suggest that the algorithms may reconstruct images of quality higher than than analytic-based algorithms from low-SNR data and/or from sparse-view data. In this work, we investigated image reconstruction from low-SNR patient-breast-CT data collected at a large number (∼500), as well as at reduced numbers, of views. The result of the study appears to indicate that optimization-based reconstructions can yield breast-CT images from low-SNR data comparable to, or better than, the corresponding FDK reconstructions.

Original language	English (US)
Title of host publication	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	8313
DOIs	https://doi.org/10.1117/12.911325
State	Published - 2012
Event	Medical Imaging 2012: Physics of Medical Imaging - San Diego, CA, United States Duration: Feb 5 2012 → Feb 8 2012

Other

Other	Medical Imaging 2012: Physics of Medical Imaging
Country	United States
City	San Diego, CA
Period	2/5/12 → 2/8/12

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
Biomaterials
Radiology Nuclear Medicine and imaging

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title = "A preliminary investigation of reduced-view image reconstruction from low dose breast CT data",

abstract = "Analytic-based algorithms such as the FDK algorithm is used currently for image reconstruction from data acquired with prototypes of dedicated breast CT scanners. In general, analytic-based algorithms require data collected at a large number (∼500) of views. In current breast-CT scans, imaging dose delivered to the patient is about the same as that used in a typical two-view mammography exam. This highly limited total imaging dose, when distributed over a large number of views in breast CT, can result in low-SNR data. There exists a renewed interest in developing optimization-based (i.e., iterative) algorithms for image reconstruction from low-SNR data and/or from sparse-view data collected at a reduced number of views. Results of recent studies on optimization-based algorithms from CT data suggest that the algorithms may reconstruct images of quality higher than than analytic-based algorithms from low-SNR data and/or from sparse-view data. In this work, we investigated image reconstruction from low-SNR patient-breast-CT data collected at a large number (∼500), as well as at reduced numbers, of views. The result of the study appears to indicate that optimization-based reconstructions can yield breast-CT images from low-SNR data comparable to, or better than, the corresponding FDK reconstructions.",

author = "Junguo Bian and Xiao Han and Kai Yang and Sidky, {Emil Y.} and Boone, {John M} and Xiaochuan Pan",

year = "2012",

doi = "10.1117/12.911325",

language = "English (US)",

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AU - Bian, Junguo

AU - Han, Xiao

AU - Yang, Kai

AU - Sidky, Emil Y.

AU - Boone, John M

AU - Pan, Xiaochuan

PY - 2012

Y1 - 2012

N2 - Analytic-based algorithms such as the FDK algorithm is used currently for image reconstruction from data acquired with prototypes of dedicated breast CT scanners. In general, analytic-based algorithms require data collected at a large number (∼500) of views. In current breast-CT scans, imaging dose delivered to the patient is about the same as that used in a typical two-view mammography exam. This highly limited total imaging dose, when distributed over a large number of views in breast CT, can result in low-SNR data. There exists a renewed interest in developing optimization-based (i.e., iterative) algorithms for image reconstruction from low-SNR data and/or from sparse-view data collected at a reduced number of views. Results of recent studies on optimization-based algorithms from CT data suggest that the algorithms may reconstruct images of quality higher than than analytic-based algorithms from low-SNR data and/or from sparse-view data. In this work, we investigated image reconstruction from low-SNR patient-breast-CT data collected at a large number (∼500), as well as at reduced numbers, of views. The result of the study appears to indicate that optimization-based reconstructions can yield breast-CT images from low-SNR data comparable to, or better than, the corresponding FDK reconstructions.

AB - Analytic-based algorithms such as the FDK algorithm is used currently for image reconstruction from data acquired with prototypes of dedicated breast CT scanners. In general, analytic-based algorithms require data collected at a large number (∼500) of views. In current breast-CT scans, imaging dose delivered to the patient is about the same as that used in a typical two-view mammography exam. This highly limited total imaging dose, when distributed over a large number of views in breast CT, can result in low-SNR data. There exists a renewed interest in developing optimization-based (i.e., iterative) algorithms for image reconstruction from low-SNR data and/or from sparse-view data collected at a reduced number of views. Results of recent studies on optimization-based algorithms from CT data suggest that the algorithms may reconstruct images of quality higher than than analytic-based algorithms from low-SNR data and/or from sparse-view data. In this work, we investigated image reconstruction from low-SNR patient-breast-CT data collected at a large number (∼500), as well as at reduced numbers, of views. The result of the study appears to indicate that optimization-based reconstructions can yield breast-CT images from low-SNR data comparable to, or better than, the corresponding FDK reconstructions.

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