Dhawan A P, Arata L
Department of Electrical and Computer Engineering, University of Cincinnati, OH.
Am J Physiol Imaging. 1992 Jul-Dec;7(3-4):210-9.
With the recent advances in medical imaging, three-dimensional anatomical and metabolic images of the brain are now available through MR/CT and PET/SPECT imaging modalities. Computerized multi-modality three-dimensional brain image registration and analysis can provide important correlated information for improving diagnosis and studying the pathology of disease. Such analysis may also provide help in planning brain surgery. Further, an anatomical model based quantification and analysis of internal structure can be used to develop a computerized anatomical atlas. Conventional anatomical atlases provide rigid spatial distribution of internal structures extracted from a single subject. The proposed computerized anatomical atlas provides probabilistic spatial distributions which can be easily updated to incorporate the variability of brain structures of subjects selected from pre-defined groups. This paper first presents a review of the current trends in knowledge-based segmentation, labeling, and analysis of MR brain images and then describes the Principal Axes Transformation based registration of three-dimensional MR brain images to develop composite models of selected internal brain structures. The composite models can be used as a computerized anatomical atlas in model-based segmentation and labeling of MR brain images. Three-dimensional labeled MR images of the brain can also be registered and correlated with PET images for analyzing the metabolic activity in the anatomically selected volume of interest. On the other hand, a volume of interest can be selected using the metabolic information and then analyzed for correlated anatomical information using the registered MR-PET images.
随着医学成像技术的最新进展，现在可以通过磁共振成像/计算机断层扫描（MR/CT）以及正电子发射断层显像/单光子发射计算机断层扫描（PET/SPECT）成像方式获得大脑的三维解剖和代谢图像。计算机化的多模态三维脑图像配准与分析可为改善疾病诊断及研究疾病病理学提供重要的相关信息。这种分析在脑外科手术规划中也可能有所帮助。此外，基于解剖模型的内部结构量化与分析可用于开发计算机化解剖图谱。传统解剖图谱提供从单个受试者提取的内部结构的刚性空间分布。所提出的计算机化解剖图谱提供概率性空间分布，其可以很容易地更新，以纳入从预定义组中选择的受试者脑结构的变异性。本文首先综述基于知识的磁共振脑图像分割、标记和分析的当前趋势，然后描述基于主轴变换的三维磁共振脑图像配准，以开发选定脑内部结构的复合模型。这些复合模型可在基于模型的磁共振脑图像分割和标记中用作计算机化解剖图谱。大脑的三维标记磁共振图像也可以进行配准，并与正电子发射断层显像（PET）图像相关联，以分析在解剖学上选定的感兴趣体积内的代谢活动。另一方面，可以使用代谢信息选择感兴趣体积，然后使用配准的磁共振-正电子发射断层显像（MR-PET）图像分析相关的解剖学信息。
