Subscription or Fee Access
The Improvement of Automatic Scanning Microscope Based on Intelligent Systems to Identify Mycobacterium Tuberculosis
This research yielded the conventional light microscope which could do screening and identification of mycobacterium tuberculosis automatically in sputum smear slide with Ziehl-Neelsen staining. The tool consists of electromechanical side which was assembled to move the X-Y direction of microscope desk automatically. The microscope was provided with the computer aided diagnose software to identify mycobacterium tuberculosis which it consists of image processing, segmentation, feature extraction, and classification methods. The most important in software development in this research is the segmentation process. It could influence the accuracy of mycobacterium tuberculosis observation. We tried some methods on segmentation in which k-Nearest Neighbors gave the better accuracy than other methods. But k-Nearest Neighbors gave the long computational times. After segmentation process, we did classification to the reddish object using neural network with feature extraction based on geometrical shape to become neural network input. The neural network gave very good accuracy 100% on classification of mycobacterium tuberculosis and not mycobacterium tuberculosis.
Microscope, image processing, segmentation, feature extraction, classification.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.