基於CT和乳房X射線像的乳房密度分析

Breast Density Analysis based on CT and Mammography Images

伊微若(Violeta Ivanova)

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/碩士(2012年)

https://doi.org/10.6342/NTU.2012.02104

摘要

乳癌是目前女性族群中最常檢驗出的癌症，也是死亡主因之一，而乳房密度被視為一項顯著風險因子，與罹患乳癌的相對風險有最強的相關性。現今最常見用於估計密度的方法為乳房攝影影像，因此乳房攝影被應用作乳房異常的一項標準參考，但是乳房密度估計值可能有顯著波動，這有一部份歸因於乳房攝影的投射性質，因此進行中的三維電腦斷層掃描(3-D CT)掃描研究正在使用定量研究衡量乳房密度，以獲得可能更一致的乳房密度分析。
在這篇論文中，我們將評估同一位病患使用乳房攝影及CT兩種不同技術的影像的密度；分析乳房密度的乳房CT影像分割技術以非網格圖像影象對位以及模糊C 平均分類法為基礎，並採用胸腔模型法進行。本次研究中所有的CT掃描均為低劑量胸腔掃描；估計2維 (2-D) 及3-D乳房攝影影像的乳房密度使用的是不同的軟體程式。乳房影像和CT的密度相關性評估則透過計算皮爾森積差相關係數完成。
分析來自12位病患的乳房掃描顯示這2種技術產生的結果具高度正相關，雖然乳房攝影被應用為標準參考，此研究結果展現X射線CT乳房成影技術在評估乳房密度上有很好的發展空間，且常用於偵測肺癌的低劑量胸部CT亦可用於預測乳房密度。

關鍵字

乳房密度分析 ； 乳房攝影 ； 3-D影像分割 ； CT ； 影像定位

並列摘要

Breast cancer is currently the most common diagnosed cancer among women and a leading cause of death. Breast density is considered a significant risk factor and it is the strongest correlation with relative risk of developing breast cancer. Nowadays, the most common approaches to estimate density are using mammographic images so that mammography has been applied as a standard reference for breast abnormalities. However, the estimates of breast density may vary significantly, in part, due to the projective nature of mammography. Therefore, ongoing studies using three-dimensional 3-D computed tomography (CT) scans are evaluating quantitatively breast density for achieving potentially more consistent breast density analysis.
In this paper, we propose to assess the densities from images of two different modalities; CT and mammography, for the same patient. We use chest body model approach for template-based breast CT segmentation method based on non-rigid image registration and a fuzzy C-mean clustering for breast densities analysis. All the CT scans, in this study, are low-dose chest scans. For the breast density estimation of the two-dimensional (2-D) and 3-D mammography images are used different software programs. The assessment of the correlation between the mammographic and CT densities was performed by computing the Pearson's correlation coefficient.
The analysis of breasts scans from 12 patients shows that the results from both modalities have high positive correlations. Although mammography has been applied as a standard reference, the results from this study demonstrate good potential for density assessment with CT x-ray and that low-dose chest CT, commonly used for lung cancer detection, could be also applied for breast density estimation.

並列關鍵字

breast density analysis ； mammography ； 3-D image segmentation ； CT ； image registration

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