Segmentation of multi-modality MR images by means of evidence theory for 3D reconstruction of brain tumors

被引：0

作者：

Capelle, AS ^{[1
]}

Colot, O ^{[1
]}

Fernandez-Maloigne, C ^{[1
]}

机构：

[1] Univ Poitiers, UMR CNRS 6615, Lab IRCOM SIC, F-86962 Futuroscope, France

来源：

2002 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS | 2002年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a segmentation scheme for Magnetic Resonance (MR) images based on a two step algorithm. The first step consists in a classification based on art evidential k-NN rule initially proposed by Denoeux. The second step allows to take into account the spatial dependence of each voxel of the MR volume in order to lead the segmentation. The goal is to locate properly tumors in MR images of brain allowing the 3D reconstruction of the different brain structures and the tumor. So, it can lead to help the clinicians to observe the tumors accurately and to follow the evolution of the tumors in multidate acquisitions of MR images.

引用

页码：773 / 776

页数：4

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