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Reseach Article

Computer-Aided Breast Tumor Segmentation

by Shweta Bhanushali, Sonia Lad, Vaibhavi Haria, Poonam Bhogale
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 19
Year of Publication: 2015
Authors: Shweta Bhanushali, Sonia Lad, Vaibhavi Haria, Poonam Bhogale
10.5120/20261-2656

Shweta Bhanushali, Sonia Lad, Vaibhavi Haria, Poonam Bhogale . Computer-Aided Breast Tumor Segmentation. International Journal of Computer Applications. 115, 19 ( April 2015), 33-36. DOI=10.5120/20261-2656

@article{ 10.5120/20261-2656,
author = { Shweta Bhanushali, Sonia Lad, Vaibhavi Haria, Poonam Bhogale },
title = { Computer-Aided Breast Tumor Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 19 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 33-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number19/20261-2656/ },
doi = { 10.5120/20261-2656 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:55:19.475974+05:30
%A Shweta Bhanushali
%A Sonia Lad
%A Vaibhavi Haria
%A Poonam Bhogale
%T Computer-Aided Breast Tumor Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 19
%P 33-36
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Breast cancer is one of the most prevalent cancers diagnosed among the middle aged women. The rate of curacy depends on how well and early the tumor has been detected. One of the most effective methods of breast tumor segmentation is by using x-ray mammography. The accuracy of the results varies with the experience of the radiologists and the quality of the mammograms. In order to overcome these drawbacks a computer aided system has been developed that can accurately identify, position and segment the tumor.

References
  1. Dr. H. B. Kekre,Tanuja K. Sarode. 2012," Two-level vector-quantization method for Codebook generation, using Kekre's Proportionate error algorithm, International Journal of Image Processing, Volume(4):Issue(1)
  2. Theodosios Goudas and Ilias Maglogiannis, "Cancer Cells Detection and Pathology Quantification Utilizing Image Analysis Techniques", 34th Annual International Conference of the IEEE EMBS San Diego, California USA, 2012.
  3. Tzu-Chuen Lu and Ching-Yun Chang, "A Survey of VQ Codebook Generation", Journal of Information Hiding and Multimedia Signal Processing, Volume 1, Number 3, 2010.
  4. Dr. H. B. Kekre, TK. Sarode, S. M. Gharge. Kekre's," Fast Codebook Generation Algorithm for Tumor Detection in Mammography Images", ICWET 2010.
  5. Manisha Sharma, Vandana Chouhan, "Objective Evaluation parameters of Image Segmentation Algorithms" , IJEAT 2012.
  6. Manoj Kumar, Poonam Saini, "Image Compression With Efficient Codebook Initialization Using LBG Algorithm", International Journal of Advanced Computer Technology, Volume 2, Number 2.
  7. Mukesh Mittal, RuchikaLamba, "Image Compression Using Vector Quantization Algorithms: A Review", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 6, 2013.
  8. Huanyi Yang, Lauren A. Christopher, Nebojsa Duric, Erik West and Predrag Bakic, "Performance Analysis of EM-MPM and K-means Clustering in 3D Ultrasound Image Segmentation", IEEE2012.
  9. P. Spandana, Dr. Kunda M. M Rao. SMIEEE, Prof. B. V. V. S. N. Prabhakar rao, Dr. Jwalasrikala, "Novel Image Processing Techniques for Early Detection of Breast Cancer, Mat lab and Lab view implementation", 2013 IEEE Point-of-Care Healthcare Technologies(PHT) Bangalore, India, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Computer-aided Tumor segmentation Thresholding LBG KPE KMeans.