Automatic Brain Tumor Segmentation Using Multi-OTSU Thresholding and Morphological Reconstruction
| Autor: | Djamel Eddine Chouaib Belkhiat, Imane Mehidi, Dalel Jabri |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
medicine.diagnostic_test
Computer science Structuring element business.industry Pattern recognition Magnetic resonance imaging 02 engineering and technology Image contrast 030218 nuclear medicine & medical imaging Image (mathematics) 03 medical and health sciences 0302 clinical medicine Otsu thresholding Region of interest 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Segmentation Artificial intelligence business Brain tumor segmentation |
| Zdroj: | Advances in Computing Systems and Applications ISBN: 9783030694173 CSA |
| DOI: | 10.1007/978-3-030-69418-0_26 |
| Popis: | Images segmentation aims to divide an image into several segments. They can be selected according to the composition of the region of interest, the types of tissues, and the functional zones [1]. In this paper, we present a new segmentation method, based on the multi-thresholding method and morphological reconstruction for brain tumor separation from Magnetic Resonance Imaging (MRI). Firstly, we use a pre-processing to enhance image contrast and quality by intensity adjustment. Secondly, the improved image is segmented using the multi-Otsu method and finally, a morphological reconstruction was performed with the appropriate structuring element parameter on the segmented image to determine the tumor. A comparison with some state-of-the-art algorithms demonstrated the efficiency of the proposed method with regard to accuracy. |
| Databáze: | OpenAIRE |
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