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11 March 2008 Interactive surface correction for 3D shape based segmentation
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Abstract
Statistical shape models have become a fast and robust method for segmentation of anatomical structures in medical image volumes. In clinical practice, however, pathological cases and image artifacts can lead to local deviations of the detected contour from the true object boundary. These deviations have to be corrected manually. We present an intuitively applicable solution for surface interaction based on Gaussian deformation kernels. The method is evaluated by two radiological experts on segmentations of the liver in contrast-enhanced CT images and of the left heart ventricle (LV) in MRI data. For both applications, five datasets are segmented automatically using deformable shape models, and the resulting surfaces are corrected manually. The interactive correction step improves the average surface distance against ground truth from 2.43mm to 2.17mm for the liver, and from 2.71mm to 1.34mm for the LV. We expect this method to raise the acceptance of automatic segmentation methods in clinical application.
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Tobias Schwarz, Tobias Heimann, Ralf Tetzlaff, Anne-Mareike Rau, Ivo Wolf, and Hans-Peter Meinzer "Interactive surface correction for 3D shape based segmentation", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69143O (11 March 2008); https://doi.org/10.1117/12.770350
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