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Digital Imaging Network-Picture Archiving and Communication System (DIN-PACS) has been the cutting edge technology in telemedicine and teleradiology world. It enables sharing and processing of patient data and images in a networked environment. This sharing implies a distributed environment where doctors and other health practitioners do not need to be physically present in the data sources in order to access them. This advantage in itself is a very economical alternative in time and money. Furthermore, digital processing enables doctors and health practitioners to acquire, examine, and even digitally manipulate data (text, images, sound, and videos). A reduced rate of image loss probability and inexpensive and fast image storage further provide attractions to digital imaging network. Until recent years, however, DIN-PACS technologies are implemented in a localized environment only, e.g., within a single hospital or clinic. The need to share and process these data in a wider area environment (e.g., inter-hospital, city-wide, state-wide, nation-wide, or even world-wide environment), especially in teleradiology discipline, prompted the concept Virtual Radiology Environment (VRE). Virtual Radiology Environment enables the networking of multiple DIN-PACS, which requires an integrated network design configured for both clinicians and radiologist needs. This dissertation presents the design specification and a CORBA-based prototype implementation of such environment.

A method is developed for pre-processing projection images for a SPECT brain imaging system. The projection images are recorded by modular gamma cameras that exhibit noisy response before processing. The image acquisition process is modeled so that the mean of the detected gamma-ray emissions is a linear transformation of the actual flux. Two models for detection are examined, one based on independent Poisson distributions and the other based on a multivariate distribution. The Expectation Maximization (EM) algorithm is used to invert the forward model to obtain a Maximum Likelihood estimate of the flux. Simulations using uniform, Gaussian and point flux patterns demonstrated that EM processing recovered improved estimates of these patterns. Processing measured images yielded improved estimates, but also revealed that both forward models are incomplete.

A study was undertaken to better characterize normal human spontaneous EEG and steady-state visually-evoked potentials (SSVEPs), and to relate these observations to theoretical models of local/global interactions within the neocortex. 131-channel scalp data were collected from normal subjects in relaxed and cognitive (mental addition) states. High priority was given throughout to data quality, artifact prevention, rigorous signal analysis, and extensive validation of methods Calculation of coherence at frequencies between 2 and 48 Hz showed mixed increases/decreases in alpha coherence, and increases in theta coherence with cognitive activity. Coherence patterns were systematically translated into valued and unvalued graphs and analyzed using tools from information theory. The resulting networks displayed high topological integration in cases of high total coherence. Comparison of graph distance with physical distance in these networks yielded evidence for binding of semi-global networks oscillating in the theta and upper alpha bands. Further study of phase information at peak alpha-band frequencies showed significant consistency of phase maps between epochs, consistent with existence of a globally resonant component in the alpha rhythm In order to further investigate these phenomena, methodology was developed and validated to accurately extract spatial spectra from high-density EEG. Frequency-wavenumber relations were identified in EEG and SSVEP, consistent with wavelike propagation of neural activity along the corticocortical fibers. Furthermore, changes observed during cognitive activity suggested a concomitant shift from global to local dynamics in some subjects Taken as a whole, these results indicate a role for global dynamics in the human alpha rhythm, and specifically suggest a mixed global/local origin for this phenomenon. The results also yield: strong evidence for wavelike propagation of the SSVEP throughout the neocortex; further evidence for a global-to-local transition during periods of increased cognitive activity; and a more complete baseline understanding of coherence in the normal human EEG. This, along with the methodological advances described, should provide a firm foundation for more effective use of scalp EEG in both clinical diagnosis and research applications / acase@tulane.edu

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