Minati L, Ghielmetti F, Ciobanu V, D'Incerti L, Maccagnano C, Bizzi A, Bruzzone M G
Scientific Direction Unit, Istituto Nazionale Neurologico C. Besta, via Celoria, 11, I-20133, Milano, Italy.
J Digit Imaging. 2007 Mar;20(1):32-41. doi: 10.1007/s10278-006-0859-2.
Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.
先进的神经成像技术，如功能磁共振成像（fMRI）、化学位移光谱成像（CSI）、扩散张量成像（DTI）和灌注加权成像（PWI），在数据存储和管理方面带来了新的挑战：会生成大量原始数据，分析结果可能取决于所使用的软件和设置，而且大多数情况下中间文件本质上不符合当前的DICOM（医学数字成像和通信）标准，因为它们包含多维复杂数组和张量数组以及各种其他类型的数据结构。本文介绍了一种软件架构，称为生物图像仓库系统（BIWS），它可以与放射学信息系统/图像存档与通信系统（RIS/PACS）系统一起使用，用于存储神经成像数据以进行研究。该系统架构的设计目的是能够根据预定义的两层分类法按诊断进行查询。发现该系统的操作影响以及熟悉基于网络的界面和分类法所需的时间是有限的。本文还提出了开发能够自动创建统计模板的模块。
