A fully automatic cardiac segmentation method using region growing technique
| Autor: | Saïd Mahmoudi, Abdelaziz Daoudi |
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| Rok vydání: | 2016 |
| Předmět: |
Segmentation-based object categorization
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Image processing Image segmentation Hough transform law.invention Region growing law Computer vision Adaptive histogram equalization Segmentation Artificial intelligence business Mathematics |
| Zdroj: | MedPRAI |
| Popis: | Automatic images segmentation is a crucial phase from image processing to image analysis; it is a subset of an expansive field of Computer Vision. In the medical field, this operation allows achieving efficient analysis of the contractile heart function, which is the main criterion used to determine the prognostic of different cardiopathies. This paper presents a fully automatic cardiac segmentation of the right ventricle (RV) based on region growing (RG) technique, which can segment the area of the RV from the basal to the apical slices at End-systolic (ES) and Enddiastolic (ED) phases. In an initial step, an adaptive histogram equalization (AHE) has been introduced as a pretreatment to improve contrast and broaden the regions having a bad distribution in image. In the next steps, the proposed method uses two algorithms in order to automate the segmentation process. The first one is the generalized Hough transform technique (GHT) applied to select the initial seed pixel, so that the RG can start growing, and the second one is an iterative threshold selection algorithm to compute the optimal threshold value for the best segmentation. The experiment results show that the proposed method is efficient in both selecting seed point and segmenting region of the RV. |
| Databáze: | OpenAIRE |
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