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Research ArticleOpen accessIn the abstractA FAST AND ACCURATE METHOD FOR AUTOMATIC CORONARY ARTERIAL TREE EXTRACTION IN ANGIOGRAMSRohollah Moosavi Tayebi, Puteri Suhaiza Binti Sulaiman, Rahmita Wirza et al.Coronary arterial tree extraction in angiograms is an essential component of each cardiac image processing system. Once physicians decide to check up coronary arteries from x-ray angiograms, extraction must be done precisely, fast, automatically and including whole arterial tree to help diagnosis or treatment during the cardiac surgical operation. This application is very helpful for the surgeon on deciding the … …Journal of Computer Science, Vol. 10, Issue 10 · 27 Jun 2014 · 8,296 accessesView PDFCite
Research ArticleOpen accessIn the abstractAN ALGORITHM FOR MINING USABLE RULES USING A HOLISTIC SWARM BASED APPROACHVeenu Mangat, Renu VigEvolutionary algorithms are capable of finding near optimal solutions to problems which are intractable to solve using conventional methods. One such problem is to accurately classify patients using rule mining methodology while controlling the size of output rules. A massive amount of data pertaining to medicine is generated and recorded daily. Uncovering useful knowledge and assisting decision makers in the … …Journal of Computer Science, Vol. 10, Issue 4 · 9 Dec 2013 · 6,667 accessesView PDFCite
Research ArticleOpen accessIn the abstractBLOOD VESSELS EXTRACTION USING MATHEMATICAL MORPHOLOGYNidhal Khdhair El Abbadi, Enas Hamood Al SaadiThe retinal vasculature is composed of the arteries and veins with their tributaries which are visible within the retinal image. The segmentation and measurement of the retinal vasculature is of primary interest in the diagnosis and treatment of a number of systemic and ophthalmologic conditions. The accurate segmentation of the retinal blood vessels is often an essential prerequisite step in … …Journal of Computer Science, Vol. 9, Issue 10 · 12 Sep 2013 · 7,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimal Approach for Medical Image AnalysisJ. Umamaheswari, G. RadhamaniProblem statement: Image segmentation is the process that subdivides an image into its constituent parts and extracts the objects. It is one of the most critical tasks in automatic image analysis because the subdivided results will affect all the subsequent processes of image analysis, such as object representation and description, feature measurement and even the following higher level tasks such … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 6 Jun 2012 · 9,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 accessIn the abstractAn Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy TechniqueS. Murugavalli, V. RajamaniImplementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,107 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Pre-processing of USF and MIAS Mammogram ImagesAyman A. AbuBaker, R. S. Qahwaji, Musbah J. Aqel et al.High quality mammogram images are high resolution and large size images. Processing these images require high computational capabilities. The transmission of these images over the net is sometimes critical especially if the diagnosis of remote radiologists is required. In this paper, a pre-processing technique for reducing the size and enhancing the quality of USF and MIAS mammogram images is introduced. … …Journal of Computer Science, Vol. 3, Issue 2 · 28 Feb 2007 · 7,167 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDeep Learning Approaches for Brain Tumor Diagnosis using Fused Layer AcceleratorMitrabinda Khuntia, Prabhat Kumar Sahu, Swagatika DeviDeep Convolutional Neural Networks (DCNNs) are an emerging field in biomedical processing. Tumor classification is a key stage in the pathology analysis process, and deep learning algorithms for brain tumor categorization have recently shown promising results. However, these approaches often require more storage and more expensive training procedures to input a large number of training variables. To address this issue, … …Journal of Computer Science, Vol. 19, Issue 2 · 19 Jan 2023 · 5,787 accessesView PDFCite