Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images

Xiaofeng Yang; Pegah Ghafourian; Puneet Sharma; Khalil Salman; Diego Martin; Baowei Fei

doi:10.1117/12.912190

Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images

Xiaofeng Yang, Pegah Ghafourian, Puneet Sharma, Khalil Salman, Diego Martin, Baowei Fei

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

30 Scopus citations

Abstract

We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.

Original language	English (US)
Title of host publication	Medical Imaging 2012
Subtitle of host publication	Image Processing
DOIs	https://doi.org/10.1117/12.912190
State	Published - 2012
Externally published	Yes
Event	Medical Imaging 2012: Image Processing - San Diego, CA, United States Duration: Feb 6 2012 → Feb 9 2012

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	8314
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2012: Image Processing
Country/Territory	United States
City	San Diego, CA
Period	2/6/12 → 2/9/12

Keywords

Dynamic contrast enhanced (DCE) MRI
Image classification
Kidney
Non-rigid image registration

ASJC Scopus subject areas

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

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10.1117/12.912190

Cite this

Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images. / Yang, Xiaofeng; Ghafourian, Pegah; Sharma, Puneet et al.
Medical Imaging 2012: Image Processing. 2012. 83140B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8314).

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

Yang, X, Ghafourian, P, Sharma, P, Salman, K, Martin, D & Fei, B 2012, Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images. in Medical Imaging 2012: Image Processing., 83140B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 8314, Medical Imaging 2012: Image Processing, San Diego, CA, United States, 2/6/12. https://doi.org/10.1117/12.912190

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abstract = "We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.",

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doi = "10.1117/12.912190",

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AU - Sharma, Puneet

AU - Salman, Khalil

AU - Martin, Diego

AU - Fei, Baowei

PY - 2012

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N2 - We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.

AB - We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.

KW - Dynamic contrast enhanced (DCE) MRI

KW - Image classification

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KW - Non-rigid image registration

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

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Nonrigid registration and classification of the kidneys in 3D dynamic contrast enhanced (DCE) MR images

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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