Data normalization method for a multisource inverse geometry CT system

Jongduk Baek, Norbert J. Pelc

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. Each source is activated sequentially and covers a small portion of the field-of-view (FOV) and a full FOV reconstruction is acquired by combining projection data from all sources. During the data acquisition, the intensity of each x-ray source could change, e.g. because of instability in the power supply, leading to artifacts in the reconstructed image. To reduce the image artifacts, we developed a data normalization algorithm for the MS-IGCT system. The projection data of each source shares an overlap region in 2D Radon space with another source. Thus, substantially same projection data can be generated from different sources at different gantry positions. Since at least one source can illuminate a reference channel and therefore its data can be easily normalized. This normalized projection data can be used to normalize the raw data of another source with which it shares an overlap region. By performing this normalization process sequentially, the intensity variations of all sources can be corrected. The proposed method was tested with Shepp-Logan phantom using 10% random source intensity fluctuations. While the reconstructed image showed image artifacts that result from uncorrected fluctuations, after applying the proposed normalization algorithm, image artifacts were removed.

Original languageEnglish
Title of host publicationMedical Imaging 2012
Subtitle of host publicationPhysics of Medical Imaging
DOIs
Publication statusPublished - 2012 May 4
EventMedical Imaging 2012: Physics of Medical Imaging - San Diego, CA, United States
Duration: 2012 Feb 52012 Feb 8

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8313
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2012: Physics of Medical Imaging
CountryUnited States
CitySan Diego, CA
Period12/2/512/2/8

Fingerprint

Artifacts
Information Storage and Retrieval
Radon
Geometry
geometry
Data acquisition
Detectors
Electric Power Supplies
X rays
artifacts
projection
X-Rays
field of view
gantry cranes
x ray sources
radon
power supplies
data acquisition

All Science Journal Classification (ASJC) codes

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

Cite this

Baek, J., & Pelc, N. J. (2012). Data normalization method for a multisource inverse geometry CT system. In Medical Imaging 2012: Physics of Medical Imaging [83132B] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8313). https://doi.org/10.1117/12.912029
Baek, Jongduk ; Pelc, Norbert J. / Data normalization method for a multisource inverse geometry CT system. Medical Imaging 2012: Physics of Medical Imaging. 2012. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE).
@inproceedings{fdc54140e5924a1f9c0769d19c20ddf0,
title = "Data normalization method for a multisource inverse geometry CT system",
abstract = "The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. Each source is activated sequentially and covers a small portion of the field-of-view (FOV) and a full FOV reconstruction is acquired by combining projection data from all sources. During the data acquisition, the intensity of each x-ray source could change, e.g. because of instability in the power supply, leading to artifacts in the reconstructed image. To reduce the image artifacts, we developed a data normalization algorithm for the MS-IGCT system. The projection data of each source shares an overlap region in 2D Radon space with another source. Thus, substantially same projection data can be generated from different sources at different gantry positions. Since at least one source can illuminate a reference channel and therefore its data can be easily normalized. This normalized projection data can be used to normalize the raw data of another source with which it shares an overlap region. By performing this normalization process sequentially, the intensity variations of all sources can be corrected. The proposed method was tested with Shepp-Logan phantom using 10{\%} random source intensity fluctuations. While the reconstructed image showed image artifacts that result from uncorrected fluctuations, after applying the proposed normalization algorithm, image artifacts were removed.",
author = "Jongduk Baek and Pelc, {Norbert J.}",
year = "2012",
month = "5",
day = "4",
doi = "10.1117/12.912029",
language = "English",
isbn = "9780819489623",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2012",

}

Baek, J & Pelc, NJ 2012, Data normalization method for a multisource inverse geometry CT system. in Medical Imaging 2012: Physics of Medical Imaging., 83132B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 8313, Medical Imaging 2012: Physics of Medical Imaging, San Diego, CA, United States, 12/2/5. https://doi.org/10.1117/12.912029

Data normalization method for a multisource inverse geometry CT system. / Baek, Jongduk; Pelc, Norbert J.

Medical Imaging 2012: Physics of Medical Imaging. 2012. 83132B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8313).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Data normalization method for a multisource inverse geometry CT system

AU - Baek, Jongduk

AU - Pelc, Norbert J.

PY - 2012/5/4

Y1 - 2012/5/4

N2 - The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. Each source is activated sequentially and covers a small portion of the field-of-view (FOV) and a full FOV reconstruction is acquired by combining projection data from all sources. During the data acquisition, the intensity of each x-ray source could change, e.g. because of instability in the power supply, leading to artifacts in the reconstructed image. To reduce the image artifacts, we developed a data normalization algorithm for the MS-IGCT system. The projection data of each source shares an overlap region in 2D Radon space with another source. Thus, substantially same projection data can be generated from different sources at different gantry positions. Since at least one source can illuminate a reference channel and therefore its data can be easily normalized. This normalized projection data can be used to normalize the raw data of another source with which it shares an overlap region. By performing this normalization process sequentially, the intensity variations of all sources can be corrected. The proposed method was tested with Shepp-Logan phantom using 10% random source intensity fluctuations. While the reconstructed image showed image artifacts that result from uncorrected fluctuations, after applying the proposed normalization algorithm, image artifacts were removed.

AB - The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. Each source is activated sequentially and covers a small portion of the field-of-view (FOV) and a full FOV reconstruction is acquired by combining projection data from all sources. During the data acquisition, the intensity of each x-ray source could change, e.g. because of instability in the power supply, leading to artifacts in the reconstructed image. To reduce the image artifacts, we developed a data normalization algorithm for the MS-IGCT system. The projection data of each source shares an overlap region in 2D Radon space with another source. Thus, substantially same projection data can be generated from different sources at different gantry positions. Since at least one source can illuminate a reference channel and therefore its data can be easily normalized. This normalized projection data can be used to normalize the raw data of another source with which it shares an overlap region. By performing this normalization process sequentially, the intensity variations of all sources can be corrected. The proposed method was tested with Shepp-Logan phantom using 10% random source intensity fluctuations. While the reconstructed image showed image artifacts that result from uncorrected fluctuations, after applying the proposed normalization algorithm, image artifacts were removed.

UR - http://www.scopus.com/inward/record.url?scp=84860359569&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860359569&partnerID=8YFLogxK

U2 - 10.1117/12.912029

DO - 10.1117/12.912029

M3 - Conference contribution

AN - SCOPUS:84860359569

SN - 9780819489623

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2012

ER -

Baek J, Pelc NJ. Data normalization method for a multisource inverse geometry CT system. In Medical Imaging 2012: Physics of Medical Imaging. 2012. 83132B. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). https://doi.org/10.1117/12.912029