Automatic pulmonary nodule detection from radiography using histograms of oriented gradients descriptors /
A chest X-ray examination is a painless, non-invasive, and cost effective medical examination performed at present day. A pulmonary nodule is a small round lesion or mass in the lungs which can be indicative of an infection or a neoplasm. Chest X-rays can be used to diagnose pulmonary nodules. State...
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| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Kuala Lumpur :
Kulliyyah of Engineering, International Islamic University Malaysia,
2015
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| Subjects: | |
| Online Access: | http://studentrepo.iium.edu.my/handle/123456789/4361 |
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| 008 | 150618t2015 my a g m 000 0 eng d | ||
| 040 | |a UIAM |b eng | ||
| 041 | |a eng | ||
| 043 | |a a-my--- | ||
| 050 | 0 | 0 | |a RC941 |
| 100 | 1 | |a Naing, Wai Yan Nyein | |
| 245 | 1 | |a Automatic pulmonary nodule detection from radiography using histograms of oriented gradients descriptors / |c by Wai Yan Nyein Naing | |
| 260 | |a Kuala Lumpur : |b Kulliyyah of Engineering, International Islamic University Malaysia, |c 2015 | ||
| 300 | |a xvi, 206 leaves : |b ill. ; |c 30cm. | ||
| 502 | |a Thesis (MSMCT)--International Islamic University Malaysia, 2015. | ||
| 504 | |a Includes bibliographical references (leaves 109-123). | ||
| 520 | |a A chest X-ray examination is a painless, non-invasive, and cost effective medical examination performed at present day. A pulmonary nodule is a small round lesion or mass in the lungs which can be indicative of an infection or a neoplasm. Chest X-rays can be used to diagnose pulmonary nodules. State-of-the-art automatic pulmonary nodule detection techniques are agonized by the problems posed by noise, local-global feature dilemma, and the bias-and-variance dilemma. To evade these problems, this project proposes a three-layered framework to perform automatic diagnosis of pulmonary nodules. The first layer performs hybrid Haar-wavelet based image enhancement and contour-based lung field segmentation. The second layer extracts histogram of oriented gradient descriptors from a pre-processed X-ray image and compresses the high-dimensional descriptors onto a low dimensional manifold using codec manifold neural network. Finally, the third layer classifies whether the X-ray contains any signs of nodules using an ensemble of partial decision trees. Experiments have been carried out on three X-ray datasets. The proposed system was found to outperform the state-of-the-art systems The results demonstrate the efficacy of the proposed nodule detection framework. The proposed pulmonary nodule detection can be integrated with the existing X-ray equipment in hospitals in order to perform rapid diagnosis. | ||
| 596 | |a 1 | ||
| 655 | 7 | |a Theses, IIUM local | |
| 690 | |a Dissertations, Academic |x Department of Mechatronics Engineering |z IIUM | ||
| 710 | 2 | |a International Islamic University Malaysia. |b Department of Mechatronics Engineering | |
| 856 | 4 | |u http://studentrepo.iium.edu.my/handle/123456789/4361 | |
| 900 | |a sbh-ls | ||
| 999 | |c 437411 |d 468323 | ||
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