超音波影像上的乳房密度分析與腋窩淋巴結狀態之預測

Breast Density Analysis and Axillary Lymph Node Status Prediction using Ultrasound Images

李衍緯(Yan-Wei Lee)

指導教授 ： 張瑞峰

國立臺灣大學/電機資訊學院/資訊工程學研究所/博士(2017年)

https://doi.org/10.6342/NTU201701447

摘要

乳癌是女性最普遍的惡性腫瘤之一，而且一直以來是世界各地女性的主要死因。許多研究指出高乳房密度的女性較低乳房密度的女性具有更高罹患乳癌的風險。因此，乳房密度被認為在乳癌風險預測上具有極大的意義。然而，本篇論文將會在自動全乳房超音波影像中使用三維的方法來計算乳房密度。
在罹患乳癌的女性中，許多的主要死因不是原發性腫瘤造成，而是癌症在遠處器官的轉移。腋窩淋巴結是否遭到轉移則是早期乳癌患者最重要的預後因素。在本研究中，提出了計算機輔助預測系統，利用乳癌超音波圖像中腫瘤周圍組織的特徵來判斷腋窩淋巴結的狀態。

關鍵字

自動全乳房超音波 ； 乳房密度分析 ； 乳癌 ； 超音波影像 ； 腋窩淋巴結狀態之預測

並列摘要

Breast cancer is one of the most common malignancies in women and it continues to be a major cause of death among women worldwide. Several studies have shown that the women with dense breasts are at higher risk than the women whose breasts are less dense. Hence, breast density has to be accepted as a clinically highly significant predictor of breast cancer risk. In this paper, we propose a three-dimension (3-D) method to estimate the breast density with automated whole breast ultrasound (ABUS).
In females with breast cancer, the major cause of death is not the primary tumor but the distant organs metastasis. The presence or absence of axillary lymph node (ALN) metastasis is the most important prognostic factor for patients with early-stage breast cancer. In this study, a computer-aided prediction (CAP) system using the tumor surrounding tissue features in ultrasound (US) images was proposed to determine the ALN status in breast cancer.

並列關鍵字

Automated Whole Breast Ultrasound ； Breast Density Analysis ； Breast Cancer ； Ultrasound Images ； Axillary Lymph Node Status Prediction

參考文獻

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