Medical image segmentation using 3D MRI data
Medical image segmentation using 3D MRI data
复制标题
使用 3D MRI 数据进行医学图像分割
DOI：
10.1117/12.2262857
复制
发表时间：
2017
影响因子：
20.6
通讯作者：
S. Agaian
中科院分区：
文献类型：
--
作者：
V. Voronin;V. Marchuk;E. Semenishchev;Yigang Cen;S. Agaian
磁共振成像（MRI）三维图像的精确分割是临床上非常有用的计算机辅助诊断（CAD）工具。从通过磁共振成像（MRI）获得的图像中准确地自动提取3D分量是一个具有挑战性的分割问题，这是由于感兴趣的小尺寸对象（例如，血管、骨骼）和复杂的周围解剖结构。我们的目标是开发一个特定的分割方案，准确地提取部分骨骼的MRI图像。本文采用一种基于改进活动轮廓法的分割算法从磁共振成像（MRI）数据集中提取骨骼的部分区域。结果表明，该方法在真实的MRI数据的现有分割方法之间的比较中表现出良好的准确性。
Precise segmentation of three-dimensional (3D) magnetic resonance imaging (MRI) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Accurate automatic extraction a 3D component from images obtained by magnetic resonance imaging (MRI) is a challenging segmentation problem due to the small size objects of interest (e.g., blood vessels, bones) in each 2D MRA slice and complex surrounding anatomical structures. Our objective is to develop a specific segmentation scheme for accurately extracting parts of bones from MRI images. In this paper, we use a segmentation algorithm to extract the parts of bones from Magnetic Resonance Imaging (MRI) data sets based on modified active contour method. As a result, the proposed method demonstrates good accuracy in a comparison between the existing segmentation approaches on real MRI data.