![](/images/graphics-bg.png)
Deformable Models for Segmentation Based on Local Analysis
Joint Authors
Vallejo, Enrique
Olveres, Jimena
Carbajal-Degante, Erik
Escalante-Ramírez, Boris
García-Moreno, Carla María
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Segmentation tasks in medical imaging represent an exhaustive challenge for scientists since the image acquisition nature yields issues that hamper the correct reconstruction and visualization processes.
Depending on the specific image modality, we have to consider limitations such as the presence of noise, vanished edges, or high intensity differences, known, in most cases, as inhomogeneities.
New algorithms in segmentation are required to provide a better performance.
This paper presents a new unified approach to improve traditional segmentation methods as Active Shape Models and Chan-Vese model based on level set.
The approach introduces a combination of local analysis implementations with classic segmentation algorithms that incorporates local texture information given by the Hermite transform and Local Binary Patterns.
The mixture of both region-based methods and local descriptors highlights relevant regions by considering extra information which is helpful to delimit structures.
We performed segmentation experiments on 2D images including midbrain in Magnetic Resonance Imaging and heart’s left ventricle endocardium in Computed Tomography.
Quantitative evaluation was obtained with Dice coefficient and Hausdorff distance measures.
Results display a substantial advantage over the original methods when we include our characterization schemes.
We propose further research validation on different organ structures with promising results.
American Psychological Association (APA)
Olveres, Jimena& Carbajal-Degante, Erik& Escalante-Ramírez, Boris& Vallejo, Enrique& García-Moreno, Carla María. 2017. Deformable Models for Segmentation Based on Local Analysis. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1189612
Modern Language Association (MLA)
Olveres, Jimena…[et al.]. Deformable Models for Segmentation Based on Local Analysis. Mathematical Problems in Engineering No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1189612
American Medical Association (AMA)
Olveres, Jimena& Carbajal-Degante, Erik& Escalante-Ramírez, Boris& Vallejo, Enrique& García-Moreno, Carla María. Deformable Models for Segmentation Based on Local Analysis. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1189612
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189612