Automatic Volumetric Liver Segmentation Using Texture Based Region Growing

被引：29

作者：

Gambino, O. ^{[1
]}

Vitabile, S. ^{[2
]}

Lo Re, G. ^{[2
]}

La Tona, G. ^{[1
]}

Librizzi, S. ^{[1
]}

Pirrone, R. ^{[1
]}

Ardizzone, E. ^{[1
]}

Midiri, M. ^{[2
]}

机构：

[1] Univ Palermo, Dipartimento Ingn Informat, Viale Sci Edificio 6 Terzo Piano, I-90128 Palermo, Italy

[2] Univ Palermo, Dipartimento Biotecnol, I-90128 Palermo, Italy

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPLEX, INTELLIGENT AND SOFTWARE INTENSIVE SYSTEMS (CISIS 2010) | 2010年

关键词：

Liver segmentation; Texture based Region Growing; CT images;

D O I：

10.1109/CISIS.2010.118

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper an automatic texture based volumetric region growing method for liver segmentation is proposed. 3D seeded region growing is based on texture features with the automatic selection of the seed voxel inside the liver organ and the automatic threshold value computation for the region growing stop condition. Co-occurrence 3D texture features are extracted from CT abdominal volumes and the seeded region growing algorithm is based on statistics in the features space. Each CT volume is composed by 230 slices, having 512 x 512 pixels as spatial resolution, and 12-bit gray level resolution. In this initial feasible study, 5 healthy volunteer acquisitions has been used. Tests have been performed on both basal phase and arterial phase images. Segmentation result shows the effectiveness of the proposed method: liver organ is correctly recognized and segmented, leaving out liver vessels form the segmented area and overcoming the "organ-splitting" problem. The goodness of the proposed method has been confirmed by manual liver segmentation results, having analogous and super-imposable behavior.

引用

页码：146 / 152

页数：7

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