Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images

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 i...

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Main Authors: Kuo-Hsien Chiang, 江國賢
Other Authors: Sheng-Fang Huang
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/01752974014938908725
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spelling ndltd-TW-099TCU056040072015-10-19T04:03:16Z http://ndltd.ncl.edu.tw/handle/01752974014938908725 Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images 應用電腦斷層影像偵測乳癌病患脊椎骨轉移之電腦輔助偵測系統 Kuo-Hsien Chiang 江國賢 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. Sheng-Fang Huang 黃聖方 2011 學位論文 ; thesis 38 en_US
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description 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.
author2 Sheng-Fang Huang
author_facet Sheng-Fang Huang
Kuo-Hsien Chiang
江國賢
author Kuo-Hsien Chiang
江國賢
spellingShingle Kuo-Hsien Chiang
江國賢
Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
author_sort Kuo-Hsien Chiang
title Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
title_short Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
title_full Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
title_fullStr Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
title_full_unstemmed Computer Aided Detection System of Vertebral Metastasis in Patients of Breast Cancer Using Computed Tomography Images
title_sort computer aided detection system of vertebral metastasis in patients of breast cancer using computed tomography images
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/01752974014938908725
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