| Summary: | 碩士 === 南臺科技大學 === 電子工程系 === 105 === Cancer is the first of top ten death causes in Taiwan, and lung cancer is the most serious cancer. LDCT (Low Dose Computed Tomography) is an effective examination technology contemporarily. However, finding the lesions heavily relies on medical physician’s judgements.
This study develops a computer software that can automatically screens pulmonary nodules from LDCT. The program, developed with Matlab, filters the LDCT figures and calculates 12 parameters of each candidate parts. The parameters are area, perimeter, HU mean, standard deviation of HU, shape, entropy, spiculation, peak, coefficient of variation of HU, standard deviation divided by area, calcify, first derivative of HU. And then, we import the parameters into an artificial neural network to identify the candidates are nodules or non-nodules. The outcomes of the artificial neural network are compared with experienced physician judgements. Employing 36 candidate figures as the test group, the neural network successfully identifies 28 non-nodules and 4 nodules, misidentifies 2 nodules as non-nodules and 2 non-nodules as nodules. The result is 66.7% sensitivity and 93.3% specificity, and the accuracy is 88.9%. Our work can help physicians with screening the chest nodules and their diagnosis and treatments.
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