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Content Provider | IET Digital Library |
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Author | Dakua, Sarada Prasad |
Abstract | Clinician-friendly methods for cardiac image segmentation in clinical practice remain a tough challenge. Larger standard deviation in segmentation accuracy may be expected for automatic methods when the input dataset is varied; also at some instances the radiologists find them hard in case any correction is desired. In this context, this study presents a semi-automatic algorithm that uses anisotropic diffusion for smoothing the image and enhancing the edges followed by a new graph-cut method, ‘AnnularCut’, for three-dimensional left ventricle (LV) segmentation from some selected slices. Unlike the conventional cellular automata, where the performance depends solely on the image features, this method simultaneously considers the minimal energy between two adjacent regions thus mitigating the convergence problem. The two main contributions in this study can be summarised as (i) a dynamic cellular automation approach to integrate the minimal energy between two distinct labels, and (ii) generation of missing contours of the subject from the selected slices using a level set method to construct the volumetric LV. Both qualitative and quantitative evaluation performed on publicly available databases reflect the potential of the proposed method. |
Starting Page | 1 |
Ending Page | 11 |
Page Count | 11 |
ISSN | 17519659 |
Volume Number | 8 |
e-ISSN | 17519667 |
Issue Number | Issue 1, Jan (2014) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/8/1 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2013.0088 |
Journal | IET Image Processing |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Algebra Anisotropic Diffusion Annular Cut Automata Theory Automatic Method Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Cardiac Image Segmentation Cellular Automata Clinical Practice Combinatorial Mathematics Computer Vision And Image Processing Technique Convergence Convergence Problem Dynamic Cellular Automation Approach Edge Enhancement Graph Theory Graph-cut Design Image Enhancement Image Feature Image Segmentation Image Smoothing Left Ventricle Segmentation Level Set Method Magnetic Resonance Image Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy MRI Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Qualitative Evaluation Quantitative Evaluation Semi-automatic Algorithm Set Theory Spectroscopy Standard Deviation Three-dimensional LV Segmentation Volumetric LV |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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