A FULLY AUTOMATED SPINAL CORD SEGMENTATION

被引：0

作者：

Jois, Subramanya S. P. ^{[1
]}

Sridhar, Harsha ^{[1
]}

Kumar, J. R. Harish ^{[1
,2
]}

机构：

[1] Indian Inst Sci, Dept Elect Engn, Bangalore, Karnataka, India

[2] Manipal Inst Technol, Dept Elect & Elect Engn, Manipal, Karnataka, India

来源：

2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018) | 2018年

关键词：

Neurological disorder; spinal cord; segmentation; active discs; region growth; MAGNETIC-RESONANCE IMAGES; MULTIPLE-SCLEROSIS; DISABILITY; ATROPHY; MODEL;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Segmentation of the spinal cord region is an imperative step in the automated analysis of neurological ailments such as multiple sclerosis. Multiple studies demonstrated the connection between progression of neurological diseases and measurements identifying with spinal cord atrophy and changes to its structure. Segmentation of spinal cord region manually or semi-automatically, can be conflicting and tedious for large datasets. We present a novel automated method, that segments the spinal cord region, utilizing circular active discs and region growth algorithm. The proposed method is validated on the Visible Human Project dataset. The results with regards to sensitivity, specificity, accuracy, Jaccard index, and Dice coefficient were 97.23%, 100%, 99.76%, 96.83%, and 98.65%, respectively. The results were observed to be highly precise in comparison to expert outlines.

引用

页码：524 / 528

页数：5

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