PubMed · 3842984
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G Wiederhold, P D Clayton. Processing biological data in real time.. https://pubmed.ncbi.nlm.nih.gov/3842984/
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Electron micrographs from serial cross-sections of 12-day-old mouse forelegs were digitized and three-dimensional reconstruction of the data was carried out on an Apple Macintosh Quadra 700 computer using a program especially designed for this purpose. Two nerve endings of the palmar net of the median nerve were visualized together with their accompanying Schwann cells and the surrounding processes of fibroblasts. Naked axons invade straightly into the embryonic connective tissue and serve as contact guidance for the Schwann cells to follow. Fibroblasts with long processes extend around the axons with a parallel orientation. Contacts between axons and fibroblasts are occasionally observed. It is unclear whether the parallel orientation of nerve endings and fibroblast extensions have any biological significance.
Computer-based data acquisition systems play an important role in clinical monitoring and in the development of new monitoring tools. LabVIEW (National Instruments, Austin, TX) is a data acquisition and programming environment that allows flexible acquisition and processing of analog and digital data. The main feature that distinguishes LabVIEW from other data acquisition programs is its highly modular graphical programming language, "G," and a large library of mathematical and statistical functions. The advantage of graphical programming is that the code is flexible, reusable, and self-documenting. Subroutines can be saved in a library and reused without modification in other programs. This dramatically reduces development time and enables researchers to develop or modify their own programs. LabVIEW uses a large amount of processing power and computer memory, thus requiring a powerful computer. A large-screen monitor is desirable when developing larger applications. LabVIEW is excellently suited for testing new monitoring paradigms, analysis algorithms, or user interfaces. The typical LabVIEW user is the researcher who wants to develop a new monitoring technique, a set of new (derived) variables by integrating signals from several existing patient monitors, closed-loop control of a physiological variable, or a physiological simulator.
The perceptual linearization of video display systems should play a significant role in medical image presentation. It maximizes the faithfulness of information transfer to the human observer; it provides a method for standardizing the appearance of images across different display devices; and it allows for calculation of the inherent contrast resolution of different display devices. This paper provides insight into the process of perceptual linearization by decomposing it into the digital driving level-to-monitor luminance relationship, the monitor luminance-to-human brightness perception relationship, and the construction of a linearization function derived from these two relationships. A discussion of previous work in these areas is given. We then compare and contrast the results of previous work with recent experiments in our laboratory and related work in vision and computer science. We conclude that (1) sufficiently good visual models exist for agreeing on a standard method of calculating the perceptual linearization function; (2) improvements in the resolution and luminance distribution of the digital-to-analog circuitry in display systems are required for medical imaging; and (3), methods for calculating a linearization remapping from a perceptual linearization function currently have significant error and should be replaced with methods that minimize perceptual error.