A collaborative framework for distributed microscopy

  • Authors:
  • B. Parvin;J. Taylor;G. Cong

  • Affiliations:
  • Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA;Lawrence Berkeley National Laboratory, Berkeley, CA

  • Venue:
  • SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
  • Year:
  • 1998

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Abstract

This paper outlines the motivation, requirements, and architecture of a collaborative framework for distributed virtual microscopy. In this context, the requirements are specified in terms of (1) functionality, (2) scalability, (3) interactivity, and (4) safety and security. Functionality refers to what and how an instrument does something. Scalability refers to the number of instruments, vendor-specific desktop workstations, analysis programs, and collaborators that can be accessed. Interactivity refers to how well the system can be steered either for static or dynamic experiments. Safety and security refers to safe operation of an instrument coupled with user authentication, privacy, and integrity of data communication.To meet these requirements, we introduce three types of services in the architecture: Instrument Services (IS), Exchange Services (ES), and Computational Services (CS). These services may reside on any host in the distributed system. The IS provide an abstraction for manipulating different types of microscopes; the ES provide common services that are required between different resources; and the CS provide analytical capabilities for data analysis and simulation. These services are brought together through CORBA and its enabling services, e.g., Event Services, Time Services, Naming Services, and Security Services.Two unique applications have been introduced into the CS for analyzing scientific images either for instrument control or recovery of a model for objects of interest. These include: in-situ electron microscopy and recovery of 3D shape from holographic microscopy. The first application provides a near real-time processing of the video-stream for on-line quantitative analysis and the use of that information for closed-loop servo control. The second application reconstructs a 3D representation of an inclusion (a crystal structure in a matrix) from multiple views through holographic electron microscopy.These application require steering external stimuli or computational parameters for a particular result. In a sense, "computational instruments" (symmetric multiprocessors) interact closely with data generated from "experimental instruments" (unique microscopes) to conduct new experiments and bring new functionalities to these instruments. Both of these features exploit high-performance computing and low-latency networks to bring novel functionalities to unique scientific imaging instruments.