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...
and Chung, P-C., “A fast algorithm for multilevel thresholding”, Journal of Information Science and Engineering 17 (5): 713-727, 2001. Available at: <https://ftp.iis.sinica.edu.tw/JISE/2001/200109_01.pdf> DOI:10.6688/JISE.2001.17.5.1 2 Tosa, Y., “Multi-Otsu Threshold”, a ...
In this paper, a new image segmentation algorithm based on Otsu thresholding. One of attractive feature of this algorithm is its ability of processing noised images. The framework contains three steps: the image to be segmented is first denoised using PCNN (Pulse Coupled Neural Network); then ...
Chinad Department of Radiology, The Second Hospital of Jilin University, Changchun 130041, Chinaa r t i c l e i n f o a b s t r a c tArticle history:Available online xxxxKeywords:Image segmentation3D Otsu thresholdingMulti-scale image representationLocal Laplacian fi lteringThresholding techni...
The effectiveness and feasibility of the proposed method are validated by comparing with the results from the traditional centroid method, the Hough circle method, the Gaussian fitting method, and the Otsu thresholding centroid method. The results show that the proposed method can realize high-...
THRESHOLDING algorithmsMAGNETIC resonance imagingIMAGE segmentationDEEP learningMACHINE learningResearch on brain tumor segmentation has been developed, ranging from threshold-based methods to the use of the deep learning algorithm. In this study, we proposed a region-based b...
Rajinikanth, V.; Raja, N.S.M.; Satapathy, S.C.; Fernandes, S.L. Otsu's multi-thresholding and active contour snake model to segment dermoscopy images. J. Med. Imag. Health Inf. 2017, 7, 1837-1840. [CrossRef]V. Rajinikanth, N. S. MadhavaRaja, S. C. Satapathy, and S. L....
Reeja, J. JackulinArun, C. H.Grenze International Journal of Engineering & Technology (GIJET)
As one of the widely used swarm-intelligence optimization algorithms, ant colony optimization (ACO) algorithm has been introduced to optimize the thresholding search process. The traditional ACO is improved in this paper to get a faster convergence speed and applied in Otsu multi-thresholds ...
This technique is; in fact, an improved version of our previously developed auto-classification algorithm by extending it by exploiting the Otsu ' s multi-level thresholding method. The detailed derivation and the brief steps of the proposed algorithm are given. The proposed algorithm is tested ...