Ruiter N V, Müller T O, Stotzka R, Gemmeke H, Reichenbach J R, Kaiser W A
Institut für Prozessdatenverarbeitung und Elektronik, Forschungszentrum Karlsruhe, Germany.
Biomed Tech (Berl). 2002;47 Suppl 1 Pt 2:644-7. doi: 10.1515/bmte.2002.47.s1b.644.
X-ray mammograms and MR volumes provide complementary information for early breast cancer diagnosis. The breast is deformed during mammography, therefore the images can not be compared directly. A registration algorithm is investigated to fuse the images automatically. A finite element simulation was applied to a MR image of an underformed breast and compared to a compressed breast using different tissue models and boundary conditions. Based on the results a set of patient data was registered. To archive the requested accuracy distinguishing between the different tissue types of the breast was not necessary. A linear elastic model was sufficient. It was possible to simulate the deformation with an average deviation of approximately of the size of a voxel in the MRI data and retrieve the position of a lesion with an error of 3.8 mm in the patient data.
乳腺X线摄影和磁共振成像容积数据为早期乳腺癌诊断提供了互补信息。乳腺在乳腺摄影过程中会发生变形,因此图像无法直接进行比较。研究了一种配准算法以自动融合图像。将有限元模拟应用于未变形乳腺的磁共振图像,并使用不同的组织模型和边界条件与压缩乳腺进行比较。基于这些结果对一组患者数据进行了配准。为达到所需的精度,无需区分乳腺的不同组织类型。线性弹性模型就足够了。能够模拟变形,在MRI数据中平均偏差约为一个体素大小,并在患者数据中以3.8毫米的误差检索病变位置。