Recent developments in Internet technology, combined with the computerization of hospital radiology departments, allow the remote viewing of medical data images. Generally, however, medical images are data intensive and the transmission of such images over a network can consumer large amounts of network resources. Previous work by Liptay et al, presented an interactive, progressive program (implemented in JAVA and requiring a web browser) that allowed the transmission of multi-resolution JPEG image data using various ROI (Region of Interest) strategies in order to minimize Internet bandwidth requirements. This work handles both 2D and 3D image data, but 3D data was treated as a sequence of 2D images, where each 2D image had to be individually requested by the system. The work described in this paper replaces the representation of 3D data as a 2D JPEG image sequence with a single block of lossy 3D image data compressed using wavelets. In a similar fashion, 2D image data is wavelet compressed. Wavelet decomposition has been shown to have consistently better image quality at high compression ratios than other lossy compression methods. We use wavelet compression in a JAVA application program on the server side to construct a lossy low resolution version of the data. As well, high resolution difference sub-blocks of data are also created by the JAVA application; a difference sub-block and the corresponding low resolution lossless data. Transmitting the low resolution image and difference sub-blocks (as requested) only requires a small fraction of the network bandwidth compared to that which would otherwise be needed to transmit the entire lossless data set. The user, via a JAVA applet on the client side, is provided with a number of methods to choose a trajectory (sequence) of regions of interest in the low resolution image. Once the region(s) of interest are chosen, the sub-blocks of image data in the various trajectories are then retrieved and integrated into the low resolution display to provide lossless reconstruction in the regions of interest. Our program significantly reduces download time since extraneous information is not transmitted.
We present a JAVA-based Interactive Progressive Local Image Transmission (IPLIT) syste for viewing large images over the bandwidth-limited WWW in 'reasonable time'. One motivation behind this research is the need for medical specialists to remotely view medical imags, in reasonable time, over the WWW. In our IPLIT system, the user employs a JAVA-based Internet browser to view and browse a low resolution image. The identification of features or regions of interest before observing those regions in detail is performed by either selecting a particular region manually via mouse or by utilizing an automatic feature-detection mode. The automatic feature-detection displays high-resolution subimages along a trajectory determined by the user-specified feature of interest. Our program handles 3D image data as a sequence of 2D images. Our IPLIT system is tested on actual MRI, CT and Ultrasound medical images obtained from the Robarts Research Institute at the University of Western Ontario, Canada. One such image was used as the test image in this paper. A few test images were borrowed from the Human Visual Project.
Previous work has resulted in a spatio-temporal edge focusing algorithm for computing noiseless well-localized edge maps by tracking edges in both scale space and time. As such, the algorithm was an extension of spatial edge focusing. In this paper, we show how the 1 pixel motion constraint used in the temporal tracking component of the original spatio- temporal edge focusing algorithm can be removed to allow multiple pixel motion between adjacent frames. Our new algorithm is based on a simple Hough transform computation. The final result is an edge detection technique that uses three adjacent images from some sequence to produce a well-localized noiseless edge map for the middle image. A noise model is not explicitly required. Rather, we define an authentic edge as an intensity discontinuity existing over a number of scales and being temporally connected in three adjacent images.