IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Endoscopic Augmented Reality for Robotically Assisted Minimally Invasive Cardiac Surgery
MIAR '01 Proceedings of the International Workshop on Medical Imaging and Augmented Reality (MIAR '01)
Stereoscopic Video Synthesis from a Monocular Video
IEEE Transactions on Visualization and Computer Graphics
Numerical methods for shape-from-shading: A new survey with benchmarks
Computer Vision and Image Understanding
Real-time deformable models for surgery simulation: a survey
Computer Methods and Programs in Biomedicine
Toward Video-Based Navigation for Endoscopic Endonasal Skull Base Surgery
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Segmentation and guidance of multiple rigid objects for intra-operative endoscopic vision
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Capsule endoscopy image analysis using texture information from various colour models
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Texture and color based image segmentation and pathology detection in capsule endoscopy videos
Computer Methods and Programs in Biomedicine
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Laparoscopic surgery is indispensable from the current surgical procedures. It uses an endoscope system of camera and light source, and surgical instruments which pass through the small incisions on the abdomen of the patients undergoing laparoscopic surgery. Conventional laparoscope (endoscope) systems produce 2D colored video images which do not provide surgeons an actual depth perception of the scene. In this work, the problem was formulated as synthesizing a stereo image of the monocular (conventional) laparoscope image by incorporating into them the depth information from a 3D CT model. Various algorithms of the computer vision including the algorithms for the feature detection, matching and tracking in the video frames, and for the reconstruction of 3D shape from shading in the 2D laparoscope image were combined for making the system. The current method was applied to the laparoscope video at the rate of up to 5 frames per second to visualize its stereo video. A correlation was investigated between the depth maps calculated with our method with those from the shape from shading algorithm. The correlation coefficients between the depth maps were within the range of 0.70-0.95 (P