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Summary
Abstract
Introduction
Protocol
Results
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医学

在检测之前乳房X光检查建筑失真<em>通过</em面向模式的>分析

Published: August 30, 2013
doi:
10.3791/50341
, ,
1Department of Electrical and Computer Engineering, Schulich School of Engineering,University of Calgary , 2Department of Radiology,University of Calgary

Summary

我们展示的结构扭曲的前乳房X线照片检测方法。面向结构采用Gabor滤波器和相图来检测辐射组织模式的网站进行分析。每个网站的特点和分类使用的措施表示spiculating模式。该方法应有助于乳腺癌的检测。

Abstract

我们展示的结构扭曲的间隔癌症病例的基础上，乳腺组织模式在乳房X线照片的取向分析前乳房X线照片检测方法。我们推测，结构扭曲修改的乳腺组织模式在X线影像的正常方向群众或肿瘤形成之前。在我们的方法的初始步骤中，导向结构在给定的乳房X光检查正在使用的Gabor滤波器和相图分析，以检测辐射或交叉组织模式的节点类网站。然后每个检测到的网站的特点是使用节点值，分形维数和度量角色散的专门用来表示与结构扭曲相关spiculating模式。

我们的方法进行了测试用的56区间的癌症病例使用的开发功能106前乳房X线照片和52 13乳房X光检查正常情况下的数据库表征结构扭曲， 通过二次判别分析模式分类，并验证与留一病人出程序。根据自由反应受试者工作特征分析的结果，我们的方法已经证明，检测结构扭曲在乳房X线照片前的能力，在关于乳腺癌的临床诊断前服用15个月（平均），用80％的敏感性每名患者5误报。

Introduction

乳腺癌是影响妇女的一大疾病，是女性1,2癌症相关死亡的第二大原因。为了改善生存的机会和受影响的患者中，通过有效的治疗在乳腺癌的早期阶段的预后，疾病需要尽可能早地检测到。在乳腺癌病例的回顾性分析，异常微妙的迹象已发现在先前获得的乳房X光检查3,4。结构扭曲为乳腺癌的可能的早期阶段，这样的一个局部的乳房X线标志，难以检测5,6。关联的图案依稀描述为与没有明确的质量可见乳房的正常结构的畸变。结构扭曲可能出现在乳房肿块或肿瘤的形成的初始阶段。我们猜测，乳房X光检查前乳腺癌c中的检测获得乌尔德包含的乳腺癌的早期阶段细微的迹象，特别是建筑的失真。

图1a示出的屏幕检测癌症的情况下的现有的X线图像。异常确定由放射科医生（JELD）的区域中都列出了一个红色的矩形。在乳房X光检查前摄于图1b所示的检测乳房X光检查24个月前。在乳房X光检查之前已经被宣布为无癌症的迹象在筛选的原始实例。在回顾性分析，并与所述检测乳房X线照片，涉及到的检测到癌症部位可疑区域相比被标记由放射科医生，并以红色概述了现有乳房X线照片。可疑区域包含结构扭曲的迹象，包括骨针。

计算机辅助诊断（CAD）技术和系统提供的潜力，在Brea的实现检测的敏感性增加ST癌症2,7〜9。然而，在与存在于对乳腺癌的其他体征，如群众和钙化的检测文献的出版物的数量的比较，只有少量的研究已经报道了结构扭曲的检测中没有一个中央大规模10-17。商业上可用的CAD系统已经被发现在结构扭曲18的检测表现不佳。研究结构扭曲的屏幕检测或间隔癌症病例3,4,19-22可以帮助开发对乳腺疾病的检测和治疗策略在早期阶段，并导致改善的前乳房X线照片检测预后的病人23。

对于实验制备的图片

实验用158 X线影像，包括56个人106前乳房X线照片进行诊断乳腺癌患者和13例正常个体52的图像。从交合卫生研究伦理委员会，医学伦理办公室，卡尔加里大学和卡尔加里地区卫生局获得伦理委员会批准为研究对象。这些图像是从屏幕测试获得：阿尔伯塔程序的早期检测乳腺癌21,24,25。

在过去的预定访问筛查方案的癌症筛查计划外的诊断之前收购的乳房X线照片被打成区间癌症病例的乳房X线照片前。相应的诊断乳房X光摄影是不允许的。除了两个106前乳房X线照片已被宣布为无患乳腺癌的迹象在他们的采集和分析的筛查方案的时候，对应的另外两个乳房X线照片的人已转交活检。癌症的诊断和前乳房X线照片之间的时间间隔范围从1.5个月s到24.5个月，平均15个月和7个月的标准偏差。所有区间的癌症病例数据库中可用的乳房X线照片前已经包含在本研究中，除了其中没有可疑的地方可确定六幅图像。

屏幕膜乳房X线照片进行数字化，在50微米和每像素12位使用Lumiscan 85激光扫描器（Lumisys，桑尼维尔，CA）的灰度分辨率的空间分辨率。专家放射科医生专门从事乳腺X线摄影（JELD）审阅所有间隔癌症病例106前乳房X线照片，并标明结构扭曲的可疑区域与矩形框的基础上对后续成像或活检可用的报告，或者通过乳房X线照片的详细检查。在106之前，X线影像在本研究中所使用的数据集，38图像有明显的结构扭曲，其余68图像包含可疑或不明确EVIDENT结构扭曲。每个乳房X光检查之前包含结构扭曲的一个站点所确定的矩形框由放射科医生得出。的平均宽度，高度，和标记的放射图像的106份可疑的区域56毫米，39毫米，和2274毫米2，用11.8毫米分别标准偏差为11.6毫米，并1073.9毫米2。

Protocol

1。方法概述在我们的程序中，乳房X光摄影结构扭曲的潜力点会自动通过定向纹理图案分析的Gabor银行的应用检测过滤器26和相位建模人像11,27。所检测的位点，然后通过提取的特征或措施的步骤进行处理来表征结构扭曲，一个训练的分类器的发展，并应用一种算法，用于模式识别或分类。该过程总结为以下步骤11,20,21： 段中使用自适应?…

Representative Results

这三个特点，即，节点值，FD和H 24 F，0.61提供AUC值，0.59和0.64时，分别各功能是用于自身。结合使用的三个特点提供更好的性能与AUC = 0.70。同的三个特征的组合中得到的FROC曲线示于图11，它表示80％的5.6帧/患者和89％的7.5帧/患者的敏感性。仅使用节点值在8.1帧/病人和89％，至13.8帧/病人提供了80％的敏感性。 FP的最终结果的减少被示于图12。</…

Discussion

我们已经提出了一系列的数字图像处理和模式识别的复杂的技术，也被称为机器学习与CAD，对结构扭曲的间隔癌症病例前乳房X线照片检测。该方法是基于存在于乳腺摄影图像的定向纹理图案的分析。我们的方法，其中包括一些在我们的相关工作提出了更多的功能，能够在不到4帧/病人22检测乳腺癌的早期迹象15个月提前临床诊断时，平均，有80％的敏感性，58。

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Disclosures

The authors have nothing to disclose.

Acknowledgements

这项工作是由来自合作研究和培训经验计划（CREATE）和发现格兰特从加拿大自然科学和工程研究理事会（NSERC）资助。

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Tags

Keywords: Architectural DistortionMammogramsOriented PatternsGabor FiltersPhase PortraitsNode ValueFractal DimensionAngular DispersionQuadratic Discriminant AnalysisFree-response Receiver Operating Characteristic
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Rangayyan, R. M., Banik, S., Desautels, J. L. Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns. J. Vis. Exp. (78), e50341, doi:10.3791/50341 (2013).
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