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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22073
標題: | 乳房斷層掃描之電腦輔助腫瘤診斷 Computer-aided Tumor Diagnosis of Breast Tomosynthesis |
作者: | Chien-Huan Yu 余鑑桓 |
指導教授: | 張瑞峰 |
關鍵字: | 乳癌,二元邏輯回歸,電腦輔助診斷,Gabor小波轉換,灰階共生矩陣,ranklet轉換,乳房斷層攝影,乳房X光影像, breast cancer,binary logistic regression,computer-aided diagnosis (CADx),Gabor,grey level co-occurrence matrix (GLCM),ranklet,tomosynthesis,mammogram, |
出版年 : | 2018 |
學位: | 碩士 |
摘要: | 對於全球女性來說,乳癌已經成為最普遍的癌症之一,同時也是癌症致死的主要原因,早期偵測可以提供更好的治療並大幅降低死亡率。早期乳癌篩檢以乳房X光攝影為主要檢查工具,近年發展新型態的乳房斷層攝影是一項三維斷層技術,有助於解決二維乳房X光影像產生的組織重疊問題。因此我們提出一個電腦輔助診斷系統,應用在乳房X光影像以及乳房斷層攝影,並比較它們的效能。電腦輔助診斷系統由二元邏輯回歸分類器建立,從乳房X光影像的ROI或乳房斷層攝影的VOI提取紋理特徵,包含灰階共生矩陣、ranklet轉換、以及Gabor小波轉換。並評估不同特徵組合的效能。電腦輔助診斷系統經由42個良性和82個惡性的腫瘤的資料庫進行驗證。由Gabor小波轉換應用在乳房斷層攝影達成最佳的效能。準確率85.48% (106/124),靈敏性86.59% (71/82),特異性83.33% (35/42),以及ROC曲線面積0.8712。總結來說,乳房斷層攝影搭配Gabor小波轉換特徵相較於乳房X光影像的分類效果更好。 Among female throughout the world, breast cancer has become one of the most common carcinomas and the leading cause of cancer-related death. Early detection can provide a better treatment and significantly reduce mortality. Currently, the most effective tool to diagnose breast cancer is mammography screening. Tomosynthesis as a three dimensional (3-D) tomographic technique can overcome the overlapping problem from superimposed tissues of two dimensional (2-D) mammography. Therefore, we proposed a computer-aided diagnosis (CADx) system implemented in tomosynthesis and also in mammography to compare their performance. The CADx system was built by binary logistic regression classifier. Texture features, including gray-level co-occurrence matrix (GLCM), ranklet, and Gabor, were extracted from user-specified regions of interest (ROIs) in mammograms or volumes of interest (VOIs) in tomosynthesis images. The performance of different combinations of features were evaluated. The CADx system was tested with a dataset of 42 benign and 82 malignant tumors. The best performance was achieved by applying Gabor feature in tomosynthesis with an accuracy of 85.48% (106/124), a sensitivity of 86.59% (71/82), a specificity of 83.33% (35/42), and an Az value of 0.8712. To summarize, tomosynthesis is more effective in classification of breast tumor with Gabor feature than mammography. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22073 |
DOI: | 10.6342/NTU201802712 |
全文授權: | 未授權 |
顯示於系所單位: | 資訊工程學系 |
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