The week's pick
Reseach Article
Cancerous Cell Detection in Bone Marrow Smear
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 134 - Number 2 |
| Year of Publication: 2016 |
| Authors: Tanuja K. Sarode, Bhavik K. Thakkar, Sanket J. Purandare, Vikas M. Gupta |
10.5120/ijca2016907815
|
Tanuja K. Sarode, Bhavik K. Thakkar, Sanket J. Purandare, Vikas M. Gupta . Cancerous Cell Detection in Bone Marrow Smear. International Journal of Computer Applications. 134, 2 ( January 2016), 17-21. DOI=10.5120/ijca2016907815
Abstract
In recent years, Cancer as a disease has grown widely and it has been the major cause of mortality in humans. In this paper the main focus is on a specific type of blood cancer known as leukemia. The detection of leukemia is done via observation of the physical properties of the cells found in the bone marrow smear. This paper proposes novel leukemia detection using discrete cosine transform (DCT), and the results obtained are compared with the well-known image segmentation and feature extraction method given in the literature. From the results it is observed that the proposed method outperforms the image segmentation in terms of accuracy by 8.5% and precision by 5.4% as compared to the existing image segmentation method.
References
- Fabio Scotti, “Automatic Morphological Analysis for Acute Leukemia Identification in Peripheral Blood Microscope Images”, CIMSA 2005 – IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Giardini Naxos, Italy, 20-22 July 2005
- J.S. Lim “Two dimensional signal and image processing” Prentice Hall 1990
- R. C. Gonzalez, R. E. Woods, S.L. Eddins, “Digital Image Processing Using MATLAB”, Pearson Prentice Hall Pearson Education, Inc., New Jersey, USA, 2004
- F. Cillesen, W. Der Meer, “Atlas of Blood Cell Differentiation”, Elsevier Science B.V., Amsterdam, The Netherlands, 1998
- Serbouti S., Duhamel A. Harms, H. Gunzer U. Aus, H.M. Mary J.-Y, Beuscart R., “Image segmentation and classification methods to detect leukemias”, Annual international conference of IEEE engineering in Medicine and Biology society, Vol.13, No.1, 1991
- Foran DJ, Comaniciu D, Meer P, Goodell LA “Computer-assisted discrimination among malignant lymphomas and leukemia using immunophenotyping, intelligent image repositories, and telemicroscopy”, IEEE Trans. Inf. Technol. Biomed., pp. 265-73, December 2000
- Piuri, F. Scotti: “Morphological Classification of Blood Leucocytes by Microscope Images” Proc. International Symposium on Computational Intelligence for Measurement Systems and Applications, Boston, MD, USA, July 2004.
- R. Donida Labati, V. Piuri, and F. Scotti, "ALL-IDB: the Acute Lymphoblastic Leukemia Image Database for Image Processing", in IEEE International Conference on Image Processing (ICIP), September 11 - 14, 2011
- Ms. Minal D. Joshi, Prof. Atul H. Karode, Prof. S.R.Suralkar “White Blood Cells Segmentation and Classification to Detect Acute Leukemia” International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)” Volume 2, Issue 3, May – June 2013.
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