| Summary: | 碩士 === 慈濟大學 === 醫學資訊學系碩士班 === 99 === Bone metastases are commonly diagnosed in patients with advanced breast cancer, especially in vertebrae. Bone metastases can appear lytic, blastic, or anywhere in a continuum between these extremes. The presence or absence of bone metastases is a critical issue in the initial staging and follow-up of breast cancer because it can directly alter the therapeutic strategy. In this paper, we aim to developing a computer-aided diagnosis system for the detection of metastasis in vertebrae at whole body CT. We developed an automated method to extract ROIs of trabecular centrum from vertebrae. We computed 11 texture features and their inter-slice differences for each ROI. Total 33 features were fed into an MLP neural network to identify whether there is any abnormality in the trabecular centrum. The average accuracy, sensitivity, and specificity were 89.73%, 85.41% and 91.84%, respectively. The FN was substantially decreased from 20.83% to 14.58% when the inter-slice difference features were used.
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