Proceedings Orcun Goksel (Ed.) ⃝c 2014 for the individual papers by the papers' authors.
Copying permitted only for private and academic purposes.
Re-publication of material from this volume requires permission by the copyright owners. ogoksel@ethz.ch VISCERAL (Visual Concept Extraction Challenge in Radiology) aims to organize series of benchmarks on the processing of large-scale 3D radiology images, by using an innovative cloud-based evaluation approach.
While a growing number of benchmark studies compare the performance of algorithms for automated organ segmentation in images with restricted eld of views, emphasis on anatomical segmentation and landmark localization in images with wide eld-of-view (e.g. showing entire abdomen, trunk, or the whole body) has been limited. VISCERAL Anatomy2 benchmark series, namely Organ Segmentation and Landmark Detection Benchmarks, aim to address this need. This ISBI VISCERAL Challenge, a part of Anatomy2 series, has been organized on May 1st 2014, within the IEEE International Symposium on Biomedical Imaging (ISBI) in Beijing, China.
The challenge participants have submitted segmentation and localization results two weeks before the challenge session, that were evaluated against test data by the organizers with results presented during the challenge session. Each participant presented his method in a 15 minute oral session during the challenge session. Participants also submitted short papers summarizing their speci c methodologies that were used to generate their results.
This volume contains two parts. The rst part consist of one paper authored by the organizers of the challenge, and the second part presents a compilation of the submissions by the challenge participants. We thank the authors for their submissions and the program committee for their hard work.
Orcun Goksel
On behalf of VISCERAL Consortium
Orcun Goksel, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland Bjoern Menze, Munich University of Technology (TUM), Germany
Allan Hanbury, Vienna University of Technology, Austria (coordinator) Henning Muller, University of Applied Sciences Western Switzerland, Switzerland Georg Langs, Medical University of Vienna, Austria Orcun Goksel, ETH Zurich, Switzerland Marc-Andre Weber, University of Heidelberg, Germany Tomas Salas Fernandez, Catalan Agency for Health Information, Assessment and Quality, Spain
Ivan Eggel, University of Applied Sciences Western Switzerland, Switzerland Katharina Grunberg, University of Heidelberg, Germany Markus Holzer, Medical University of Vienna, Austria Andras Jakab, Medical University of Vienna, Austria Oscar Jimenez, University of Applied Sciences Western Switzerland, Switzerland Georgios Kontokotsios, Vienna University of Technology, Austria Markus Krenn, Medical University of Vienna, Austria Roger Schaer, University of Applied Sciences Western Switzerland, Switzerland Abdel Aziz Taha, Vienna University of Technology, Austria Marianne Winterstein, University of Heidelberg, Germany
Rule-Based Ventral Cavity Multi-Organ Automatic Segmentation in CT Scans
Assaf B. Spanier, Leo Joskowicz Automatic Liver Segmentation Using Multiple Prior Knowledge Models and
Cheng Huang, Xuhui Li, Fucang Jia Automatic Multi-Organ Segmentation Using Fast Model Based Level Set
Chunliang Wang, Orjan Smedby
Orcun Goksel, Tobias Gass, Gabor Szekely 6 16 22 25 32