Segmentation of MR Brain images with Bias Artifact

被引：0

作者：

Ardizzone, Edoardo ^{[1
]}

Pirrone, Roberto ^{[1
]}

Gambino, Orazio ^{[1
]}

Alagna, Francesco ^{[1
]}

机构：

[1] Univ Palermo, Dept Comp Sci, I-90133 Palermo, Italy

来源：

2009 9TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND APPLICATIONS IN BIOMEDICINE | 2009年

关键词：

RF-Inhomogeneity; bias; halo; segmentation; MRI; C-MEANS ALGORITHM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Brain MR Images corrupted by RF-Inhomogeneity (bias artifact) exhibit brightness variations across the image. As a consequence, a standard Fuzzy C-Means (fern) segmentation algorithm may fail. In this work we show a new general-purpose bias removing algorithm, which can be used as a pre-processing step for a fern segmentation. We also compare our experimental results with the ones achieved by using (ED)-D-2-HUM filter, showing an improvement in brain segmentation and bias removal.

引用

页码：353 / 356

页数：4

共 16 条

[1] A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data [J].