AUTOMATIC IMAGE MATCHING FOR BREAST CANCER DIAGNOSTICS BY A 3D DEFORMATION MODEL OF THE MAMMA
AUTOMATIC IMAGE MATCHING FOR BREAST CANCER DIAGNOSTICS BY A 3D DEFORMATION MODEL OF THE MAMMA
复制标题
通过乳房 3D 变形模型进行乳腺癌诊断的自动图像匹配
DOI：
10.1515/bmte.2002.47.s1b.644
复制
发表时间：
2002
影响因子：
10.6
通讯作者：
Werner A. Kaiser
中科院分区：
文献类型：
--
作者：
Nicole V. Ruiter;T. Muller;R. Stotzka;Hartmut Gemmeke;Jürgen R. Reichenbach;Werner A. Kaiser
X射线乳房X线照片和MR容积为早期乳腺癌诊断提供了补充信息。乳房X线摄影时乳房会变形，因此无法直接比较图像。研究了一种图像自动融合的配准算法。将有限元模拟应用于发育不良乳房的MR图像，并使用不同的组织模型和边界条件与受压乳房进行比较。根据结果，登记了一组患者数据。为了达到要求的准确度，无需区分不同的乳腺组织类型。线性弹性模型就足够了。可以模拟具有大约MRI数据中的体素大小的平均偏差的变形，并且可以在患者数据中以3.8mm的误差检索病变的位置。
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.
DOI：
10.1115/1.2798314
发表时间：
1998-04-01
影响因子：
1.7
作者：
Guldberg, RE;Hollister, SJ;Charras, GT
通讯作者：
Charras, GT