Sketch-Based Editing Tools for Tumour Segmentation in 3D Medical Images
Article first published online: 13 AUG 2013
© 2013 The Authors Computer Graphics Forum © 2013 The Eurographics Association and John Wiley & Sons Ltd.
Computer Graphics Forum
Volume 32, Issue 8, pages 144–157, December 2013
How to Cite
Heckel, F., Moltz, J. H., Tietjen, C. and Hahn, H. K. (2013), Sketch-Based Editing Tools for Tumour Segmentation in 3D Medical Images. Computer Graphics Forum, 32: 144–157. doi: 10.1111/cgf.12193
- Issue published online: 27 NOV 2013
- Article first published online: 13 AUG 2013
- Computer Graphics [I.3.5]: Computational Geometry and Object ModellingCurve;
- and object representations; Computer Graphics [I.3.6]: Methodology and TechniquesInteraction techniques; Image Processing and Computer Vision [I.4.6]: Segmentation
In the past years sophisticated automatic segmentation algorithms for various medical image segmentation problems have been developed. However, there are always cases where automatic algorithms fail to provide an acceptable segmentation. In these cases the user needs efficient segmentation editing tools, a problem which has not received much attention in research. We give a comprehensive overview on segmentation editing for three-dimensional (3D) medical images. For segmentation editing in two-dimensional (2D) images, we discuss a sketch-based approach where the user modifies the segmentation in the contour domain. Based on this 2D interface, we present an image-based as well as an image-independent method for intuitive and efficient segmentation editing in 3D in the context of tumour segmentation in computed tomography (CT). Our editing tools have been evaluated on a database containing 1226 representative liver metastases, lung nodules and lymph nodes of different shape, size and image quality. In addition, we have performed a qualitative evaluation with radiologists and technical experts, proving the efficiency of our tools.