首页> 美国卫生研究院文献>Medical Physics >An ellipse-fitting based method for efficient registration of breast masses on two mammographic views
【2h】

An ellipse-fitting based method for efficient registration of breast masses on two mammographic views

机译:基于椭圆拟合的方法在两个乳房X线照片上有效定位乳房肿块

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

When reading mammograms, radiologists routinely search for and compare suspicious breast lesions identified on two corresponding craniocaudal (CC) and mediolateral oblique (MLO) views. Automatically identifying and matching the same true-positive breast lesions depicted on two views is an important step for developing successful multiview based computer-aided detection (CAD) schemes. The authors developed a method to automatically register breast areas and detect matching strips of interest used to identify the matched mass regions depicted on CC and MLO views. The method uses an ellipse based model to fit the breast boundary contour (skin line) and set a local Cartesian coordinate system for each view. One intersection point between the major/minor axis and the fitted ellipse perimeter passed through breast boundary is selected as the origin and the majoraxis and the minoraxis of the ellipse are used as the two axis of the Cartesian coordinate system. When a mass is identified on one view, the scheme computes its position in the local coordinate system. Then, the distance is mapped onto the local coordinate of the other view. At the end of the mapped distance a registered centerline of the matching strip is created. The authors established an image database that includes 200 test examinations each depicting one verified mass visible on the two views. They tested whether the registered centerline identified on another view can be used to locate the matched mass region. The experiments show that the average distance between the mass region centers and the registered centerlines was ±8.3 mm and in 91% of testing cases the registered centerline actually passes through the matched mass regions. A matching strip width of 47 mm was required to achieve 100% sensitivity for the test database. The results demonstrate the feasibility of the proposed method to automatically identify masses depicted on CC and MLO views, which may improve future development of multiview based CAD schemes.
机译:在阅读乳房X光照片时,放射科医生会例行搜索并比较在两个相应的颅尾(CC)和中外侧斜(MLO)视图上发现的可疑乳腺病变。自动识别和匹配在两个视图上描绘的相同的真实阳性乳腺病变是开发成功的基于多视图的计算机辅助检测(CAD)方案的重要步骤。作者开发了一种方法,可以自动注册乳房区域并检测匹配的感兴趣条带,以识别CC和MLO视图上描绘的匹配的肿块区域。该方法使用基于椭圆的模型来拟合乳房边界轮廓(皮肤线),并为每个视图设置局部笛卡尔坐标系。选择长/短轴与经过乳房边界的拟合椭圆周长之间的一个交点作为原点,并将椭圆的长轴和短轴用作笛卡尔坐标系的两个轴。当在一个视图上识别出质量时,该方案将计算其在局部坐标系中的位置。然后,将距离映射到另一个视图的局部坐标上。在映射距离的末尾,将创建匹配条的已注册中心线。作者建立了一个图像数据库,其中包含200个测试检查,每个测试检查都描述了在两个视图上可见的一个已验证质量。他们测试了在另一个视图上标识的已注册中心线是否可用于定位匹配的质量区域。实验表明,质量区域中心与对齐的中心线之间的平均距离为±8.3 mm,在91%的测试案例中,对齐的中心线实际上通过了匹配的质量区域。要使测试数据库达到100%的灵敏度,需要匹配的条带宽度为47 mm。结果证明了该方法自动识别CC和MLO视图上描绘的质量的可行性,这可能会改善基于多视图的CAD方案的未来发展。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号