Paing, May

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Paing, May
Alternative Name
Paing, May Phu
Paing, May Phyu
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Email
may.pa@kmitl.ac.th

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    Item type:Publication,
    A Study of Pulmonary Nodules from Multi-slice Computed Tomography Using 3-D Structure
    (2018-06-21)
    Paing, May Phu
    ;
    Choomchuay, Somsak
    Multi-slice CT screening is an auspicious imaging test to detect the lung cancer. Formation of the pulmonary nodules in the lungs is the first suspicious sign of the lung cancer. The nodules appear as round or irregular shaped spots having size up to 30 mm on the CT scan. As the rate of cancer cases increases day by day, the manual detection of pulmonary nodules becomes a struggling way for the radiologists. The proposed method aims to develop an automated system to detect the pulmonary nodules using image processing techniques. Moreover, the needs of the conventional 2D detection are figured out and compensated by creating 3D structure.
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    Classification of margin characteristics from 3D pulmonary nodules
    (2017-12-19)
    Paing, May Phu
    ;
    Choomchuay, Somsak
    Detection of pulmonary nodules has played a significant role in lung cancer diagnosis because nodules are the first suspicious symptoms for the likelihood of cancer. Margin characteristics of the pulmonary nodules provide essential radiological features to determine the possibility of malignancy. In general, benign nodules hold quite smooth margins whilst malignant ones hold irregular margins. The main objective of this research is to classify different margin types of pulmonary nodules by observing the 3D structure. Nodule candidates from 2D lung CT slices are segmented firstly and then stacked to form a 3D image. Geometric features of the 3D nodule are extracted and fed into the support vector machine (SVM) classifier to classify the margin types. The proposed method can provide the classification accuracy of 90.9%.