A Study on efficient algorithms for automatic three-dimensional brain image analysis

自动三维脑图像分析的高效算法研究

• 批准号: 12680358
• 负责人: TAKAHASHI Kei
• 金额: $ 1.34万
• 依托单位: Iwate Medical University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2000
• 资助国家: 日本
• 起止时间: 2000 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12680358/
• 关键词: segmentation; brain image; database; MRI; ゼグメンテーション; アルゴリズム

The objective of our research project was to find efficient medical image processing algorithms for the practical use of image diagnoses and neuroclinical researches. In the previous study, we developed a PC-based brain image database system, and applied it to neuro-clinical research for localizing the spatial distribution of pyramidal nerve fibers in the pons. In this research, we improved the system by adding the direct image datasets from the newly installed MRI equipment with high magnetic field of 3.0 Tesla, and implementing a neural-network-based algorithm for segmentation of small anatomical structures in th brain. Each patient data consisted of image datasets and numerical information. The direct image datasets could be acquired on line with connection to the imagine equipments via local area network.Novel 3-D algorithms for MR-MR, MR-PET, PET-PET, and CT-PET registration were introduced. Efficient algorithms for detecting brain surfaces and extracting sulci and gyri based on artificial neural network were implemented to reconstruct precise brain images. All these steps were of segmentation procedures could be automatically carried out. Our next goal is to automatically segment the cerebellum, the hippocampus, and the corpus callosum.

我们研究项目的目标是寻找有效的医学图像处理算法，用于图像诊断和神经临床研究的实际应用。在之前的研究中，我们开发了基于PC的脑图像数据库系统，并将其应用于神经临床研究，以定位脑桥中锥体神经纤维的空间分布。在这项研究中，我们通过添加来自新安装的具有 3.0 特斯拉高磁场的 MRI 设备的直接图像数据集来改进系统，并实施基于神经网络的算法来分割大脑中的小型解剖结构。每个患者数据由图像数据集和数字信息组成。通过局域网连接到成像设备可以在线获取直接图像数据集。介绍了用于MR-MR、MR-PET、PET-PET和CT-PET配准的新型3D算法。采用基于人工神经网络的高效大脑表面检测和脑沟提取算法，重建精确的大脑图像。所有这些步骤都是分割程序可以自动执行的。我们的下一个目标是自动分割小脑、海马体和胼胝体。

项目成果

K.Takahashi, Y.Ohtawara, Y.Miura: "Efficient Segmentation Algorithm for Localizing Lesion Sites in Medical Images"Proc. Of 10th Medical Informatics. 993-993 (2001)

K.Takahashi、Y.Ohtawara、Y.Miura：“用于定位医学图像中病变部位的高效分割算法”Proc。

K.Takahashi,H.Yonezawa,Y.Miura: "Efficient Segmentation Algorithm for Localizing Lesion Sites in Medical Images"Medinfo'2001 Congress (London, Great Britain,2001,September). (2001)

K.Takahashi、H.Yonezawa、Y.Miura：“用于定位医学图像中病变部位的高效分割算法”Medinfo2001 年大会（英国伦敦，2001 年 9 月）。

K.Takahashi, H.Yonezawa: "Algorithms for Medical Image Analysis -(I)-"Annual Report of Iwate Medical University, School of Liberal Arts and Sciences. 36. 77-85 (2001)

K.Takahashi、H.Yonezawa：“医学图像分析算法-(I)-”岩手医科大学文理学院年度报告。

Y.Miura, K.Nishiyama: "Complete orthogonal decomposition homomorphisms between matrix ordered Hibert spaces"Proc. Amer. Math. Soc.. 129. 1137-1141 (2001)

Y.Miura，K.Nishiyama：“矩阵有序 Hibert 空间之间的完全正交分解同态”Proc。

Y.Miura: "Complete order isomorphisms between non-commutative L2-spaces"Mathematica Scandinavia. 87. 64-72 (2000)

Y.Miura：“非交换 L2 空间之间的完全顺序同构”Mathematica Scandinavia。