Work

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

Year: 2012

Type: conference-paper

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.

Source: Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

DOI: 10.1117/12.912190

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

Institutions: Emory University, Georgia Institute of Technology, Winship Cancer Institute

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Cancer Institute, National Center for Research Resources