首页> 外文会议>Conference on Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 20080217-19; San Diego,CA(US) >Towards Registration of Temporal Mammograms by Finite Element Simulation of MR Breast Volumes
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Towards Registration of Temporal Mammograms by Finite Element Simulation of MR Breast Volumes

机译:通过MR乳房体积的有限元模拟,对时间乳腺X光照片进行配准

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Performing regular mammographic screening and comparing corresponding mammograms taken from multiple views or at different times are necessary for early detection and treatment evaluation of breast cancer, which is key to successful treatment. However, mammograms taken at different times are often obtained under different compression, orientation, or body position. A temporal pair of mammograms may vary significantly due to the spatial disparities caused by the variety in acquisition environments, including 3D position of the breast, the amount of pressure applied, etc. Such disparities can be corrected through the process of temporal registration. We propose to use a 3D finite element model for temporal registration of digital mammography. In this paper, we apply patient specific 3D breast model constructed from MRI data of the patient, for cases where lesions are detectable in multiple mammographic views across time. The 3D location of the lesion in the breast model is computed through a breast deformation simulation step presented in our earlier work. Lesion correspondence is established by using a nearest neighbor approach in the uncompressed breast volume. Our experiments show that the use of a 3D finite element model for simulating and analyzing breast deformation contributes to good accuracy when matching suspicious regions in temporal mammograms.
机译:进行常规的乳房X光检查并比较从多个角度或在不同时间拍摄的相应X光照片对于乳腺癌的早期发现和治疗评估是必要的,这是成功治疗的关键。但是,通常在不同的压缩,方向或身体位置下获得在不同时间拍摄的乳房X线照片。由于由采集环境中的变化引起的空间差异(包括乳房的3D位置,所施加的压力等),时间上的乳房X线照片对可能会发生显着变化。可以通过时间配准的过程来校正此类差异。我们建议使用3D有限元模型进行数字乳腺X线摄影的时间配准。在本文中,我们应用了根据患者的MRI数据构建的患者特定的3D乳房模型,用于在一段时间内可以在多个乳房X线照片中检测到病变的情况。乳房模型中病变的3D位置是通过我们早期工作中介绍的乳房变形模拟步骤计算出来的。通过在未受压的乳房体积中使用最近邻方法建立病变对应关系。我们的实验表明,在匹配乳房X线照片中的可疑区域时,使用3D有限元模型来模拟和分析乳房变形有助于提高准确性。

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