Visual Comparison of 3D Medical Image Segmentation Algorithms Based on Statistical Shape Models
3D medical image segmentation is needed for diagnosis and treatment. As manual segmentation is very costly, automatic segmentation algorithms are needed. For finding best algorithms, several algorithms need to be evaluated on a set of organ instances. This is currently difficult due to dataset size and complexity.
In this paper, we present a novel method for comparison and evaluation of several algorithms that automatically segment 3D medical images. It combines algorithmic data analysis with interactive data visualization. A clustering algorithm identifies regions of common quality across the segmented data set for each algorithm. The comparison identifies best algorithms per region. Interactive views show the algorithm quality.
We applied our approach to a real-world cochlea dataset, which was segmented with several algorithms. Our approach allowed segmentation experts to compare algorithms on regional level and to identify best algorithms per region.
KeywordsMedical image segmentation Visual comparison Visual analytics Segmentation evaluation
- 1.Becker, M., Kirschner, M., Sakas, G.: Segmentation of risk structures for otologic surgery using the probabilistic active shape model (PASM), 9036, 90360O–90360O-7 (2014)Google Scholar
- 10.Klemm, P., Lawonn, K., Rak, M., Preim, B., Toennies, K.D., Hegenscheid, K., Völzke, H., Oeltze, S.: Visualization and analysis of lumbar spine canal variability in cohort study data. In: Proceedings of the International Workshop on Vision, Modeling and Visualization, pp. 121–128 (2013)Google Scholar
- 12.Luboschik, M., Radloff, A., Schumann, H.: A new weaving technique for handling overlapping regions. In: Proceedings of the International Conference on Advanced Visual Interfaces, AVI 2010, pp. 25–32. ACM, New York (2010). http://doi.acm.org/10.1145/1842993.1842999
- 13.Schmidt, J., Preiner, R., Auzinger, T., Wimmer, M., Gröller, M.E., Bruckner, S.: Ymca - your mesh comparison application. In: IEEE VIS 2014. IEEE Computer Society, Nov 2014Google Scholar