Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4964816 | Computers in Biology and Medicine | 2017 | 32 Pages |
Abstract
In recent years, computed tomography (CT) has become a standard technique in cardiac imaging because it provides detailed information that may facilitate the diagnosis of the conditions that interfere with correct heart function. However, CT-based cardiac diagnosis requires manual segmentation of heart cavities, which is a difficult and time-consuming task. Thus, in this paper, we propose a novel technique to segment endocardium and epicardium boundaries based on a 2D approach. The proposal computes relevant information of the left ventricle and its adjacent structures using the Hermite transform. The novelty of the work is that the information is combined with active shape models and level sets to improve the segmentation. Our database consists of mid-third slices selected from 28Â volumes manually segmented by expert physicians. The segmentation is assessed using Dice coefficient and Hausdorff distance. In addition, we introduce a novel metric called Ray Feature error to evaluate our method. The results show that the proposal accurately discriminates cardiac tissue. Thus, it may be a useful tool for supporting heart disease diagnosis and tailoring treatments.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Jimena Olveres, Rodrigo Nava, Boris Escalante-RamÃrez, Enrique Vallejo, Jan Kybic,