MAP MRF joint segmentation and registration of medical images

被引：65

作者：

Wyatt, PP ^{[1
]}

Noble, JA ^{[1
]}

机构：

[1] Univ Oxford, Dept Engn Sci, Med Vis Lab, Oxford, England

来源：

MEDICAL IMAGE ANALYSIS | 2003年 / 7卷 / 04期

基金：

英国工程与自然科学研究理事会;

关键词：

segmentation; registration; joint; combined;

D O I：

10.1016/S1361-8415(03)00067-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problems of segmentation and registration are traditionally approached individually, yet the accuracy of one is of great importance in influencing the success of the other. In this paper, we aim to show that more accurate and robust results may be obtained through seeking a joint solution to these linked processes. The outlined approach applies Markov random fields in the solution of a maximum a posteriori model of segmentation and registration. The approach is applied to synthetic and real MRI data. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：539 / 552

页数：14

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