No abstract

No abstract

No abstract

In this study, the pattern-reversal visual evoked potentials (PRVEP's) collected from normal and demented subjects are investigated by applying the quadratic spline wavelet analysis. The data are decomposed into six octave frequency bands. For quantitative purposes, the wavelet coefficients in the residual waveform representing the delta-theta band activity (0-8 Hz) are explored to characterize the (N70-P100-N130) complex. Specifically, the coefficients corresponding to the location of N70, P100, and N130 peaks are investigated for their sign in order to test whether they represent a consistent (N70-P100-N130) complex in the averaged waveform. Waveforms with normal latency (N70-P100-N130) complex are observed to have positive second, negative third, and positive fourth coefficients in amplitude in their residual scale standing for the delta-theta (0-8 Hz) band activity. The method allows for the analysis of oscillatory-phase behavior of the normal and pathological PRVEP's in their delta-theta band based on a few quantitative measures consistent with the time-frequency occurrence of the major components of the evoked potential.

Computer aided fusion of multi modality medical images provides a very promising diagnostic tool with numerous clinical applications. The objective of this paper is to present an overview of medical imaging fusion techniques with an emphasis on the use of neural network algorithms. Case studies derived from oncology (data level fusion), microscopy and ultrasound imaging (feature level and decision level fusion), and lesion placement in pallidotomy (data level fusion) are presented. It is anticipated that these tools will help the physician towards a more realistic and quantitative, assessment of disease.