Abstract
While a growing number of benchmark studies compare the performance of algorithms for automated organ segmentation or lesion detection in images with restricted fields of view, few efforts have been made so far towards benchmarking these and related routines for the automated identification of bones, inner organs and relevant substructures visible in an image volume of the abdomen, the trunk or the whole body. The VISCERAL project has organized a series of benchmark editions designed for segmentation and landmark localization in medical images of multiple modalities, resolutions and fields of view acquired during daily clinical routine work. Participating groups are provided with data and computing resources on a cloud-based framework, where they can develop and test their algorithms, the submitted executables of which are then run and evaluated on unseen test data by the VISCERAL organizers.
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The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 318068 (VISCERAL).
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Goksel, O., Foncubierta-Rodríguez, A. (2017). VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localization: Tasks and Results. In: Hanbury, A., Müller, H., Langs, G. (eds) Cloud-Based Benchmarking of Medical Image Analysis. Springer, Cham. https://doi.org/10.1007/978-3-319-49644-3_7
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