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132 results for “CT Image Segmentation”
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Research ArticleOpen accessEvery word in the titleReal-Time Endoscopic Image Semantic Segmentation for Efficient Polyp IdentificationM. Al-AsliThe advancement of endoscopic procedures has significantly enhanced diagnostic capabilities in polyp identification and removal, which is critical for colorectal cancer prevention. However, the success of these procedures hinges on the accuracy and speed of real-time image analysis. Traditional image processing methods often fail to provide timely and precise segmentation of endoscopic images. This paper presents the implementation of endoscopic … …Journal of Computer Science, Vol. 21, Issue 10 · 10 Dec 2025 · 2,397 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleLocal Features Supported by the Complement Feature for Image SegmentationSalah AmeerAn Eigen formulation is proposed for image thresholding/segmentation. A vector composed of local features, normalized intensity of each pixel and that of the neighboring pixels, is used to represent each pixel. A “complement” component is appended to this vector to produce a “unit” vector. The auto-correlation matrix is computed for each pixel in the image using this unit vector. The … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 7 Jul 2020 · 6,602 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIMAGE SEGMENTATION WITH ARTIFICIAL NEURAL NETWORK FOR NUTRIENT DEFICIENCY IN COTTON CROPMaicon A. Sartin, Alexandre C.R. Da Silva, Claudinei KappesThe leaf analysis in a crop can present the need of a nutrient determined in the plant. The macronutrients deficiency in the cotton crop can be identified by specific type of colors variation by leaves images. Early identification of macronutrients deficiency can help in the growing suitable of the crop and reduce the use of agricultural inputs. This study investigates … …Journal of Computer Science, Vol. 10, Issue 6 · 4 Feb 2014 · 6,800 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAmeliorate Fuzzy C-Means: An Ameliorate Fuzzy C-Means Clustering Algorithm for CT-Lung Image SegmentationJ. Bridget Nirmala, S. GowriEffective and efficient image segmentation acts as a preliminary stage for the computer-aided diagnosis of medical images. For image segmentation, many FCM-based clustering techniques have been proposed. Regrettably, the existing FCM technique does not generate accurate and standardized segmentation results. This is due to the noise present in the image as well as the random initialization of membership values for … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 1 Oct 2013 · 6,819 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Exponential Particle Swarm Optimization K-Means Algorithm for Efficient Image SegmentationK. M. Murugesan, S. PalaniswamiThe introduction of unsupervised learning techniques like K-means inside the domain of Image Processing plays a vital role in Image Segmentation. The hybridization of this Algorithm by using Swarm Intelligent techniques further more improves the efficiency. Various works on hybridization of Particle Swarm Optimization (PSO) with K-means have been proposed and are found to be efficient in Image Segmentation. However, … …Journal of Computer Science, Vol. 8, Issue 11 · 25 Oct 2012 · 7,141 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSegmentation of Medical Image using Clustering and Watershed AlgorithmsM.C. Jobin Christ, R.M.S. ParvathiProblem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 8,780 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleObject Recognition Based on Image Segmentation and ClusteringS. Thilagamani, N. ShanthiProblem statement: This study deals with object recognition based on image segmentation and clustering. Acquiring prior information of an image is done via two separate processes. Approach: The first process deals with detecting object parts of an image and integration of detected parts into several clusters. All these cluster centers form the visual words. The second process deals with over … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 7,074 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Approach to Medical Image SegmentationNandagopalan Shanmugam, Adiga B. Suryanarayana, Sudarshan TSB et al.Problem statement: Segmentation is a vital aspect of medical imaging. It aids in the visualization of medical data and diagnostics of various diseases. Ultrasound image segmentation, in particular echocardiographic image segmentation, is required to identify the regions of interest such as Left Ventricle (LV) and other cardiac cavities. Existing methods do not address the drawbacks of speed and quality of … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,214 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Approach for 3D Range Image Segmentation using Gradient MethodDina A. Hafiz, Walaa M. Sheta, Sahar Bayoumi, Bayumy A.B. YoussefProblem statement: Segmentation of 3D range images is widely used in computer vision as an essential pre-processing step before the methods of high-level vision can be applied. Segmentation aims to study and recognize the features of range image such as 3D edges, connected surfaces and smooth regions. Approach: This study presents new improvements in segmentation of terrestrial 3D range images … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 19,592 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRange Image Segmentation by Randomized Region Growing and Bayesian Edge RegularizationSmaine Mazouzi, Mohamed BatoucheWe presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,924 accessesView PDFCite