The week's pick
Random Articles
Reseach Article
Malaria Slaides Segmentation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 182 - Number 19 |
| Year of Publication: 2018 |
| Authors: Ruaa N. Youns, Majid D. Youns |
10.5120/ijca2018917946
|
Ruaa N. Youns, Majid D. Youns . Malaria Slaides Segmentation. International Journal of Computer Applications. 182, 19 ( Oct 2018), 7-10. DOI=10.5120/ijca2018917946
Abstract
The analysis of blood cells in a microscopic image can provide useful information about a person's health. In particular, the red blood cell analysis abnormalities can detect diseases this diseases is important such as malaria effectively. The images of blood, acquired by a microscope, which are connected with digital camera, are analyses by the computer to diagnosis or can be facilely. Transferred to clinical centers of liquid blood samples. Malaria is an infectious disease transmitted by mosquitoes of animals and humans caused by parasites (a species of microorganisms) of the Plasmodium genus . Infections begin through the bite of infected female mosquitoes, sometimes this infection leads to death, so you must find a way to help detect malaria. This document shows how to improve the image of microscopic and filter the not necessary parts, and identify the red blood cells in each image; each red blood cell is separated into a separate image.
References
- Lu´ıs, R., Jos´e, M., Correia, d. C. , Dirk, E., Jaime S. C. 2016. Automated detection of malaria parasites on thick blood smears via mobile devices. International Conference On Medical Imaging Understanding and Analysis.
- Pramit, G., Debotosh, B., Mita N.and Dipak, K. B. Medical Aid for Automatic Detection of Malaria.
- Muhammad, I. R. 2015. automatic detection and classification of malarial parasite . International Journal of Biometrics and Bioinformatics (IJBB), Volume (9) : Issue (1).
- Courosh, M. et. all . Computer-Automated Malaria Diagnosis and Quantitation.
- Arash, M. , Tooraj, A., Morteza, I. 2013. Automatic Malaria Diagnosis System.
- Ravi, S., A M Khan, 2013. Morphological Operations for Image Processing.
- Rafael G. ,digital image processing.
- Megha Goyal. 2011. Morphological Image Processing . IJCST Vol. 2, Iss ue 4, Oct . – Dec...
- Lifeng, H., Yuyan, C., Kenji, S. 2012. A New Two-Scan Algorithm for Labeling connected Components in Binary Images . Proceedings of the World Congress on Engineering Vol II ,.
- Hannan, S. Markku T.1988. Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees.
- Michael, B. D., Hannan, S., Markku, T. 1992. A General Approach to Connected-Component Labeling for Arbitrary Image Representations
- Weijie, C., Maryellen L. G., Ulrich, B. 2006. A Fuzzy C-Means (FCM)-Based Approach for Computerized Segmentation of Breast Lesions in Dynamic Contrast-Enhanced MR Images1 .
- Kesheng, W. ,Wendy K., Jacqueline, C. and Arie S., Using Bitmap Index for Interactive Exploration of Large Datasets. U.S. Department of Energy under Contract No. DE-AC03-76SF00098.
Index Terms
Keywords