圖像處理和特征分析在評估乳腺癌近期發病風險中的應用

鄭斌

摘要： 圖像處理和特征分析在乳腺癌早期診斷中發揮著重要作用。為了將一個基于左右乳腺X光片圖像密度特征不對稱性的圖像特征分析方法應用于乳腺癌近期發病風險的預測，訓練開發了一個以多圖像特征相融合的人工智能分辨模型來預測每個婦女在近期（比如，在最近一次的良性檢測以后2年之內）由醫學影像檢測出來的早期癌癥的風險程度。介紹這一個新癌癥風險預測模型的基本原理，演示一個新型的人機交互式的計算機輔助圖像特征分析和計算的工作平臺。初步實驗證明，應用這一個基于醫學圖像特征定量分析的模型能夠取得比采用現行其他已知的乳腺癌風險因子有著顯著提高的對于近期乳腺癌發病風險的預測精度，這將為建立更有效的個性化乳腺癌普查提供依據和幫助。

關鍵詞： 醫學圖像處理； 醫學圖像標志物； 乳腺X光圖像特征的定量分析； 近期乳腺癌風險評估； 計算機輔助檢測

中圖分類號： TP751 文獻標志碼： A doi： 10.3969/j.issn.1005-5630.2016.03.001

文章編號： 1005-5630（2016）03-0189-11

Abstract： Medical image processing and quantitative feature analysis play an important role in accurate detection of early breast cancer.In order to apply a new image feature analysis method based on the detection of the bilateral mammographic density and tissue asymmetry to effectively predict the near-term risk of the individual women developing breast cancer，our research group recently developed and tested a new multiple image feature based model to predict the risk or likelihood of a woman having or developing an image detectable early breast cancer in the near-term （i.e.，within the 2 years after a negative mammography screening）.In this review paper，we introduce the basic concept of this new image feature based risk prediction model，and demonstrate a graphic user interface （GUI） platform of interactively applying this new risk prediction model to process negative screening mammograms.Our preliminary testing results using several image datasets have demonstrated that applying this new risk prediction model could yield significantly higher discriminatory power in predicting near-term breast cancer risk than using other existing breast cancer risk factors and prediction models.If successful，applying our new model has potential to help establish a new and more effective personalized breast cancer screening paradigm in the future.

Keywords： medical image processing； medical image markers； quantitative mammographic image feature analysis； near-term breast cancer risk prediction model； computer-aided detection （CAD）

Introduction

Medical imaging using X-ray，ultrasound，magnetic resonance and other imaging modalities plays a critical role in many diseases including cancer screening，detection，diagnosis，and prognosis or treatment efficacy evaluation.However，accurately and consistently reading and interpreting medical images by the radiologists still faces a number of challenges in the clinical practice due to the large inter-reader variability and lack of quantitative assessment capability.Hence，developing computer-aided image processing and quantitative image feature analysis methods has been attracting extensive research interest in medical imaging fields.This review article introduces and discusses an example of applying a new computer-aided X-ray mammographic image processing scheme to build a unique near-term breast cancer risk prediction model，which aims to help improve efficacy of breast cancer screening.