ArticleInternational journal of computer assisted radiology and surgery2015
CranialCloud: a cloud-based architecture to support trans-institutional collaborative efforts in neurodegenerative disorders.
Article in International journal of computer assisted radiology and surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting response to psychiatric surgery: a systematic review of neuroimaging findings.Journal of psychiatry & neuroscience : JPN · 2020Pooled it
- Prediction of viral symptoms using wearable technology and artificial intelligence: A pilot study in healthcare workers.PloS one · 2021Article
- The Role of Large-Scale Data Infrastructure in Developing Next-Generation Deep Brain Stimulation Therapies.Frontiers in human neuroscience · 2021Article
- A Driving-Force Predictor for Estimating Pathway Activation in Patient-Specific Models of Deep Brain Stimulation.Neuromodulation : journal of the International Neuromodulation Society · 2019Article
- Effects of surgical targeting in laser interstitial thermal therapy for mesial temporal lobe epilepsy: A multicenter study of 234 patients.Epilepsia · 2019Article
- Proceedings of the Sixth Deep Brain Stimulation Think Tank Modulation of Brain Networks and Application of Advanced Neuroimaging, Neurophysiology, and Optogenetics.Frontiers in neuroscience · 2019Article
- Clinically Significant Visual Deficits after Laser Interstitial Thermal Therapy for Mesiotemporal Epilepsy.Stereotactic and functional neurosurgery · 2019Article
- Neuroethics of Neuromodulation: An Update.Current opinion in biomedical engineering · 2018Article
- Pallidal stimulation in Parkinson disease differentially modulates local and network β activity.Journal of neural engineering · 2018Article
- Quantifying axonal responses in patient-specific models of subthalamic deep brain stimulation.NeuroImage · 2018Article
- Analytical modeling and feasibility study of a multi-GPU cloud-based server (MGCS) framework for non-voxel-based dose calculations.International journal of computer assisted radiology and surgery · 2017Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeNeurological 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.
methodsIn 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.
resultsWe discuss the current state of the system that gathers data for more than 1,600 patients and how we envision it to grow.
conclusionWe 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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.