PURPOSE: Neurological diseases have a devastating impact on millions of individuals and their families. These diseases will continue to constitute a significant research focus for this century. The search for effective treatments and cures requires multiple teams of experts in clinical neurosciences, neuroradiology, engineering, and industry. Hence, the need to communicate a large amount of information with accuracy and precision is more necessary than ever for this specialty. METHODS: In this paper, we present a distributed system that supports this vision, which we call the CranialVault Cloud (CranialCloud). It consists in a network of nodes, each with the capability to store and process data, that share the same spatial normalization processes, thus guaranteeing a common reference space. We detail and justify design choices, the architecture and functionality of individual nodes, the way these nodes interact, and how the distributed system can be used to support inter-institutional research. RESULTS: We discuss the current state of the system that gathers data for more than 1,600 patients and how we envision it to grow. CONCLUSION: We contend that the fastest way to find and develop promising treatments and cures is to permit teams of researchers to aggregate data, spatially normalize these data, and share them. The CranialVault system is a system that supports this vision.
PURPOSE:Neurological diseases have a devastating impact on millions of individuals and their families. These diseases will continue to constitute a significant research focus for this century. The search for effective treatments and cures requires multiple teams of experts in clinical neurosciences, neuroradiology, engineering, and industry. Hence, the need to communicate a large amount of information with accuracy and precision is more necessary than ever for this specialty. METHODS: In this paper, we present a distributed system that supports this vision, which we call the CranialVault Cloud (CranialCloud). It consists in a network of nodes, each with the capability to store and process data, that share the same spatial normalization processes, thus guaranteeing a common reference space. We detail and justify design choices, the architecture and functionality of individual nodes, the way these nodes interact, and how the distributed system can be used to support inter-institutional research. RESULTS: We discuss the current state of the system that gathers data for more than 1,600 patients and how we envision it to grow. CONCLUSION: We contend that the fastest way to find and develop promising treatments and cures is to permit teams of researchers to aggregate data, spatially normalize these data, and share them. The CranialVault system is a system that supports this vision.
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