神经信息学
云计算
计算机科学
吞吐量
可执行文件
服务器
软件
服务(商务)
分布式计算
软件工程
操作系统
数据科学
经济
经济
无线
作者
Susumu Mori,Dan Wu,Can Ceritoglu,Yue Li,Anthony Kolasny,Marc Vaillant,Andréia V. Faria,Kenichi Oishi,Michael I. Miller
出处
期刊:Computing in Science and Engineering
[Institute of Electrical and Electronics Engineers]
日期:2016-09-01
卷期号:18 (5): 21-35
被引量:134
摘要
Image analysis tools for brain magnetic resonance imaging (MRI) have become increasingly important for computer-aided diagnosis that involves large amounts of medical image data. The authors of this article have endeavored to develop software tools to serve the clinical research community, starting with a stand-alone executable, hybrid local computation model for today's modern architecture of cloud services, which they call MRICloud. MRICloud provides a high-throughput neuroinformatics platform for automated brain MRI segmentation and analytical tools for quantification via distributed remote computation and Web-based user interfaces. There are several key, inherent advantages to a cloud-based software as a service--in particular, how it improves the efficiency of software implementation, upgrades, and maintenance. The client-server model is also ideal for high-performance computing, allowing for distribution of computational servers across the world. This article introduces the basic functions and utilities of MRICloud, its developmental history and future perspectives, its infrastructures, and the benefits of this cloud service framework.
科研通智能强力驱动
Strongly Powered by AbleSci AI