Efficient transmission of compressed data for remote volume visualization

Abstract

One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.

Sistemas de microscopía virtual: análisis y perspectivas

“…El J2K ofrece la posibilidad de acceder de manera rápida y flexible a la información de la imagen, debido a las diferentes representaciones que permite el codificador y a la posibilidad de escalamiento de los datos comprimidos (27). El estándar J2K se ha convertido en un formato de compresión ampliamente utilizado en aplicaciones médicas (1,16,(27)(28)(29).…”

“…Por otra parte, varios usuarios se pueden conectar al mismo servidor y solicitar la misma imagen, con lo cual el uso de los recursos disponibles es aún más limitado. Se han introducido diferentes estrategias de aceleración en la literatura (17,18,28,32), con el objetivo de optimizar el uso de estos recursos. Las estrategias de caché y prefetching han demostrado una mejora importante en los tiempos de navegación (17,18).…”

3-D Scalable Medical Image Compression With Optimized Volume of Interest Coding

“…Recently, a number of medical image compression methods that support VOI coding have been proposed [10]- [13]. In [10], the authors presented a compression method based on JPEG2000 that supports prioritized VOI coding based on the anatomical tissues depicted in a 3-D medical image.…”

“…In [10], the authors presented a compression method based on JPEG2000 that supports prioritized VOI coding based on the anatomical tissues depicted in a 3-D medical image. The method employs a one-dimensional DWT (1D-DWT) along the slice direction with JPEG2000 encoding of the resulting transform slices.…”

“…In order to attain optimized VOI coding at any bit-rate, the proposed method also employs after compression, an optimization technique that maximizes the reconstruction quality of the VOI, while allowing for the decoding of background information with peripherally increasing quality around the VOI. The proposed method is different from the method in [10], where the VOI coding procedure is tissue-based, the relative importance of a specific sub-band is empirically assigned, and the entropy coding of wavelet coefficients is performed using 2-D contexts. Our proposed method is also different from the VOI coding method proposed in [11], where the background information is only decoded after the VOI is fully decoded, which prevents observing the position of the VOI within the original 3-D image.…”