Deteksi Tb Paru Berdasar Ciri Statistis Histogram Citra Sinar-X

Rohmah, Ratnasari Nur (2018) Deteksi Tb Paru Berdasar Ciri Statistis Histogram Citra Sinar-X. Disertasi thesis, Universitas Muhammadiyah Surakarta.

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Currently conducted in the hospital, a manual diagnosis of pulmonary TB based on visual observation of the doctor on the X-ray image has disadvantages due to radiologist’s subjectivity and an obstacle when the ratio of the number of radiologists to patients is insufficient. This research is aimed at developing pulmonary TB detection methods based on statistical features of digital X-ray image histogram by using computer. The detection steps includes: histogram equalization, ROI template-based image segmentation, feature extraction of statistical feature image histogram using PCA transformation, and classification using Mahalanobis distance-based classifiers. This research employed textural features as a basis for classifying the images as TB or non-TB. Five patterns of ROI template candidates were created using thresholding techniques on average normal reference images. Textural features were calculated by measuring the statistical feature of image histogram on the ROI images. The features were then extracted by using PCA transformation with dimension reduction. Every method on each step of detection process was then tested to see the performance of each method used in the detection process. The results of the test indicated the histogram equalization method and the appropriate use of ROI template gave a positive contribution in the textural feature measurement. The application of PCA transformation in feature extraction and combined with Mahalanobis distance-based classifier function also gave positive contribution and produced fairly good accuracy in the detection test of Xray images. Those results are true for primary data. In addition to indicating the benefits of application of histogram equalization and transformation PCA, the tests on secondary data obtained from other researchers also conducted. The experimental result on secondary data created opportunities for further research in the data handling from different data sources and on different levels of disease

Item Type: Karya ilmiah (Disertasi)
Additional Information: Dosen Progdi Teknik Elektro Universitas Muhammadiyah Surakarta
Uncontrolled Keywords: pulmonary TB, X-ray images, PCA, histogram, Mahalanobis distance.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Fakultas Teknik > Teknik Elektro
Depositing User: Cahyana K. Widada
Date Deposited: 20 Jul 2020 06:47
Last Modified: 20 Jul 2020 06:47

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