&lt;title&gt;Visible Human Slice Web Server: a first assessment&lt;/title&gt;

Hersch, Roger D.; Gennart, Benoit A.; Figueiredo, O.; Mazzariol, Marc; Tárraga, Joaquín; Vetsch, S.; Messerli, Vincent; Welz, R.; Bidaut, Luc

doi:10.1117/12.373466

Cited by 14 publications

(12 citation statements)

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“…7 On the Internet, the interesting image retrieval applications are those implemented on the World Wide Web. [20][21][22][23] In this context, the nature of the images stored in collections is unknown a priori. We are therefore interested in heterogeneous image collections rather than domain-specific collections.…”

Section: Scopementioning

confidence: 99%

<title>Benchmark for image retrieval using distributed systems over the Iinternet: BIRDS-I</title>

Günther

Beretta

2000

SPIE Proceedings

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Comparing the performance of CBIR (Content-Based Image Retrieval) algorithms is difficult. Private data sets are used so it is controversial to compare CBIR algorithms developed by different researchers. Also, the performance of CBIR algorithms is usually measured on an isolated, well-tuned PC or workstation. In a real-world environment, however, the CBIR algorithms would only constitute a minor component among the many interacting components needed to facilitate a useful CBIR application e.g., Web-based applications on the Internet. The Internet, being a shared medium, dramatically changes many of the usual assumptions about measuring CBIR performance. Any CBIR benchmark should be designed from a networked systems standpoint. Networked system benchmarks have been developed for other applications e.g., text retrieval, and relational database management. These benchmarks typically introduce communication overhead because the real systems they model are distributed applications e.g., an airline reservation system. The most common type of distributed computing architecture uses a client/server model. We present our implementation of a client/server CBIR benchmark called BIRDS-I (Benchmark for Image Retrieval using Distributed Systems over the Internet) to measure image retrieval performance over the Internet. The BIRDS-I benchmark has been designed with the trend toward the use of small personalized wireless-internet systems in mind. Web-based CBIR implies the use of heterogeneous image sets and this, in turn, imposes certain constraints on how the images are organized and the type of performance metrics that are applicable. Surprisingly, BIRDS-I only requires controlled human intervention for the compilation of the image collection and none for the generation of ground truth in the measurement of retrieval accuracy. Benchmark image collections need to be evolved incrementally toward the storage of millions of images and that scaleup can only be achieved through the use of computeraided compilation. Finally, the BIRDS-I scoring metric introduces a tightly optimized image-ranking window, which is important for the future benchmarking of large-scale personalized wireless-internet CBIR systems.

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Section: Scopementioning

confidence: 99%

<title>Benchmark for image retrieval using distributed systems over the Iinternet: BIRDS-I</title>

Günther

Beretta

2000

SPIE Proceedings

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“…The plane P containing the directrix can be specified by using the same user interface as the one used for the extraction of oblique planar slices. 3 The directrix itself needs to be defined as a two-dimensional ͑2D͒ curve on plane P. This can be done for example by defining a spline by means of interpolation points. Due to the simplicity of their specification, spline-based cylindric surfaces are particularly well-suited for unfolding and visualization.…”

Section: Developable Surfaces and Cylindersmentioning

confidence: 99%

“…The use of integer-based discrete geometry calculations facilitates the parallelization of the algorithm and enables access to 3D volumes striped across several disks. Surface extraction is available on the Web ͑http://visiblehuman.epfl.ch͒, in addition to slice extraction, 3 slice animation extraction, 4 real-time navigation, 5 and interactive construction of anatomic structures. 6 In Sec.…”

Section: Introductionmentioning

confidence: 99%

Parallel unfolding and visualization of curved surfaces extracted from large three-dimensional volumes

Figueiredo

Hersch

2002

J. Electron. Imaging

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Abstract. Although many three-dimensional (3D) medical imaging visualization methods exist, 3D volume slicing remains the most commonly used technique for visualizing medical data from modalities such as CT, MRI, and PET. We propose to extend the possibilities of oblique slicing to developable curved surfaces that can be flattened and displayed in two dimensions without deformation. Such surfaces can be used to follow curved anatomical structures while preserving distance metrics at visualization time. They may also be useful for the staging of tumors, i.e., to evaluate the spatial extension of a tumor. We propose an out of core algorithm that runs in parallel on a multi-PC architecture and is able to extract surfaces from very large 3D datasets such as the visible human data set (man: 13 GB, woman: 49 GB). Experimental performance results are presented which demonstrate that parallel surface extraction is scalable and has a reasonable overhead compared with traditional oblique planar slicing. Surface extraction is made available to the public as one of the services offered by EPFLs visible human web server (http://visiblehuman.epfl.ch).

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“…The Visible Human Slice and Surface Server, which went online in 1999, added access to arbitrarily oriented and positioned slices and surfaces, as well as to slice sequence animations. 3 These applications require the user to define the position and orientation of each slice; each application takes a few seconds to present the results.…”

mentioning

confidence: 99%