A MRI-CT Prostate Registration Using Sparse Representation Technique

被引：2

作者：

Yang, Xiaofeng ^{[1
,2
]}

Jani, Ashesh B. ^{[1
,2
]}

Rossi, Peter J. ^{[1
,2
]}

Mao, Hui ^{[2
,3
]}

Curran, Walter J. ^{[1
,2
]}

Liu, Tian ^{[1
,2
]}

机构：

[1] Emory Univ, Dept Radiat Oncol, Atlanta, GA 30322 USA

[2] Emory Univ, Winship Canc Inst, Atlanta, GA 30322 USA

[3] Emory Univ, Dept Radiol & Imaging Sci, Atlanta, GA 30322 USA

来源：

MEDICAL IMAGING 2016: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING | 2016年 / 9786卷

关键词：

MRI-CT registration; image-guided intervention; prostate cancer; IMAGE REGISTRATION; CANCER DETECTION; FOCAL THERAPY; SEGMENTATION; LOCALIZATION; COMBINATION;

D O I：

10.1117/12.2216430

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

In this paper, we propose a new patch-based initial deformation prediction framework for MRI-CT prostate registration. The sparse representation technique is used to estimate the initial deformation between MRI and CT images in a patch-wise fashion. This method can be further refined by many of the existing registration methods after providing a predicted field for initializing prostate MRI-CT registration. Our registration technique was validated with a clinical study of 9 prostate-cancer patients. Our proposed registration was compared with the current intensity-based registration method. This initial investigation of the prostate MRI-CT registration approach using patch-based deformation demonstrated its clinical feasibility as well as its accuracy.

引用

页数：8

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