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Paper Title
Detection of Renal Tumours using Artificial Neural Network and Image Processing of CT Scan
Authors
  Gary Mendonca

Abstract
Renal tumour segmentation and investigation is an imperative advance for specialists in understanding the phase of the disease and deciding the technique for treatment. This paper inspects a novel way to recognize and additionally examine the renal disease tumours using an efficient algorithm. The algorithm has been utilized to pre-process and segment the image for better perception and division of a visible tumour. The pre-processing includes a hybrid channel for noise removal and picture upgrade. An artificial neural system has likewise been utilized by methods of Hybrid Self Organizing Maps which we have used for the clustering of the image information and accordingly featuring the distinguished region. The right output obtained by the medical group is then compared with the resultant image with the end goal to make a better calculation and for the algorithm to aptly understand the influenced regions in the human body and help in better perception of the tumour. We then apply a region growing technique which searches for regions with similar intensity and sections out the tumour from the prepared image.

Keywords- Image Processing, Renal Tumour, ANN, CT filter, Region Growing, SOM
Publication Details
Unique Identification Number - IJEDR1804059
Page Number(s) - 314-320
Pubished in - Volume 6 | Issue 4 | November 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Gary Mendonca,   "Detection of Renal Tumours using Artificial Neural Network and Image Processing of CT Scan", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.314-320, November 2018, Available at :http://www.ijedr.org/papers/IJEDR1804059.pdf
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