Book ChapterDOI
Automatic Brain Tumor Segmentation Using Multi-OTSU Thresholding and Morphological Reconstruction
Imane Mehidi,Djamel Eddine Chouaib Belkhiat,Dalel Jabri +2 more
- pp 289-300
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TLDR
In this paper, a new segmentation method, based on the multi-thresholding method and morphological reconstruction for brain tumor separation from Magnetic Resonance Imaging (MRI), was presented.Abstract:
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.read more
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Proceedings ArticleDOI
SwinT-Unet: Hybrid architecture for Medical Image Segmentation Based on Swin transformer block and Dual-Scale Information
TL;DR: This paper deals with designing a hybrid method of medical image segmentation using a dual-Scale encoder–Swin transformer U-shaped architecture (SwinT-Unet), which demonstrated more efficiency than the results of some other current methods.
References
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