Contour‐based Interface for Refining Volume Segmentation

Medical volume images contain ambiguous and low‐contrast boundaries around which existing fully‐ or semiautomatic segmentation algorithms often cause errors. In this paper, we propose a novel system for intuitively and efficiently refining medical volume segmentation by modifying multiple curved contours. Starting with segmentation data obtained using any existing algorithm, the user places a three‐dimensional curved cross‐section and contours of the foreground region by drawing a cut stroke, and then modifies the contours referring to the cross‐section. The modified contours are used as constraints for deforming a boundary surface that envelops the foreground region, and the region is updated by that deformed boundary. Our surface deformation algorithm seamlessly integrates detail‐preserving and curvature‐diffusing methods to keep important detail boundary features intact while obtaining smooth surfaces around unimportant boundary regions. Our system supports topological manipulations as well as contour shape modifications. We illustrate the feasibility of our system by providing examples of its application to the extraction of bones, muscles, kidneys with blood vessels, and bowels.

[1]  Olga Sorkine-Hornung,et al.  On Linear Variational Surface Deformation Methods , 2008, IEEE Transactions on Visualization and Computer Graphics.

[2]  Maneesh Agrawala,et al.  Interactive video cutout , 2005, SIGGRAPH 2005.

[3]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[4]  Jerry L. Prince,et al.  A Survey of Current Methods in Medical Image Segmentation , 1999 .

[5]  Lu Liu,et al.  VolumeViewer: An Interactive Tool for Fitting Surfaces to Volume Data , 2009 .

[6]  Tim McInerney,et al.  SketchSurfaces: Sketch-Line Initialized Deformable Surfaces for Efficient and Controllable Interactive 3D Medical Image Segmentation , 2007, ISVC.

[7]  Marc Alexa,et al.  FiberMesh: designing freeform surfaces with 3D curves , 2007, ACM Trans. Graph..

[8]  Marc Alexa,et al.  FiberMesh: designing freeform surfaces with 3D curves , 2007, SIGGRAPH 2007.

[9]  Frank Nielsen,et al.  Volume catcher , 2005, I3D '05.

[10]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[11]  Kwan-Liu Ma,et al.  A novel interface for higher-dimensional classification of volume data , 2003, IEEE Visualization, 2003. VIS 2003..

[12]  Takeo Igarashi,et al.  As-rigid-as-possible shape manipulation , 2005, SIGGRAPH '05.

[13]  Anthony J. Sherbondy,et al.  Fast volume segmentation with simultaneous visualization using programmable graphics hardware , 2003, IEEE Visualization, 2003. VIS 2003..

[14]  Marc Alexa,et al.  A sketch-based interface for detail-preserving mesh editing , 2005, SIGGRAPH 2005.

[15]  Christian Rössl,et al.  Laplacian surface editing , 2004, SGP '04.

[16]  Xun Wang,et al.  A comparative study of deformable contour methods on medical image segmentation , 2008, Image Vis. Comput..

[17]  Marc Alexa,et al.  A sketch-based interface for detail-preserving mesh editing , 2007, SIGGRAPH Courses.

[18]  O. Sorkine Differential Representations for Mesh Processing , 2006 .

[19]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[21]  Lu Liu,et al.  Surface Reconstruction From Non‐parallel Curve Networks , 2008, Comput. Graph. Forum.

[22]  Takeo Igarashi,et al.  As-rigid-as-possible shape manipulation , 2005, ACM Trans. Graph..

[23]  Maneesh Agrawala,et al.  Interactive video cutout , 2005, ACM Trans. Graph..