Paper
12 March 2013 Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging
Bingxiong Lin, Yu Sun, Xiaoning Qian
Author Affiliations +
Abstract
Robust feature point matching for images with large view angle changes in Minimally Invasive Surgery (MIS) is a challenging task due to low texture and specular reflections in these images. This paper presents a new approach that can improve feature matching performance by exploiting the inherent geometric property of the organ surfaces. Recently, intensity based template image tracking using a Thin Plate Spline (TPS) model has been extended for 3D surface tracking with stereo cameras. The intensity based tracking is also used here for 3D reconstruction of internal organ surfaces. To overcome the small displacement requirement of intensity based tracking, feature point correspondences are used for proper initialization of the nonlinear optimization in the intensity based method. Second, we generate simulated images from the reconstructed 3D surfaces under all potential view positions and orientations, and then extract feature points from these simulated images. The obtained feature points are then filtered and re-projected to the common reference image. The descriptors of the feature points under different view angles are stored to ensure that the proposed method can tolerate a large range of view angles. We evaluate the proposed method with silicon phantoms and in vivo images. The experimental results show that our method is much more robust with respect to the view angle changes than other state-of-the-art methods.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bingxiong Lin, Yu Sun, and Xiaoning Qian "Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging", Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 867112 (12 March 2013); https://doi.org/10.1117/12.2007687
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Cited by 4 scholarly publications.
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KEYWORDS
3D modeling

3D image processing

Natural surfaces

Surgery

Heart

Stereoscopic cameras

Feature extraction

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