Biomedical subjects

Danail Stoyanov

Publications and source records attributed to Danail Stoyanov.

4 recordsLinked to original sources

PubMed2005

Gaze-contingent soft tissue deformation tracking for minimally invasive robotic surgery.

The introduction of surgical robots in Minimally Invasive Surgery (MIS) has allowed enhanced manual dexterity through the use of microprocessor controlled mechanical wrists. Although fully autonomous robots are attractive, both ethical and legal barriers can prohibit their practical use in surgery. The purpose of this paper is to demonstrate that it is possible to use real-time binocular eye tracking for empowering robots with human vision by using knowledge acquired in situ. By utilizing the close relationship between the horizontal disparity and the depth perception varying with the viewing distance, it is possible to use ocular vergence for recovering 3D motion and deformation of the soft tissue during MIS procedures. Both phantom and in vivo experiments were carried out to assess the potential frequency limit of the system and its intrinsic depth recovery accuracy. The potential applications of the technique include motion stabilization and intra-operative planning in the presence of large tissue deformation.

Artificial Intelligence↗

PubMed2005

Laparoscope self-calibration for robotic assisted minimally invasive surgery.

For robotic assisted minimal access surgery, recovering 3D soft tissue deformation is important for intra-operative surgical guidance, motion compensation, and prescribing active constraints. We propose in this paper a method for determining varying focal lengths of stereo laparoscope cameras during robotic surgery. Laparoscopic images typically feature dynamic scenes of soft-tissue deformation and self-calibration is difficult with existing approaches due to the lack of rigid temporal constraints. The proposed method is based on the direct derivation of the focal lengths from the fundamental matrix of the stereo cameras with known extrinsic parameters. This solves a restricted self-calibration problem, and the introduction of the additional constraints improves the inherent accuracy of the algorithm. The practical value of the method is demonstrated with analysis of results from both synthetic and in vivo data sets.

Algorithms↗

PubMed2005

Soft-tissue motion tracking and structure estimation for robotic assisted MIS procedures.

In robotically assisted laparoscopic surgery, soft-tissue motion tracking and structure recovery are important for intraoperative surgical guidance, motion compensation and delivering active constraints. In this paper, we present a novel method for feature based motion tracking of deformable soft-tissue surfaces in totally endoscopic coronary artery bypass graft (TECAB) surgery. We combine two feature detectors to recover distinct regions on the epicardial surface for which the sparse 3D surface geometry may be computed using a pre-calibrated stereo laparoscope. The movement of the 3D points is then tracked in the stereo images with stereo-temporal constrains by using an iterative registration algorithm. The practical value of the technique is demonstrated on both a deformable phantom model with tomographically derived surface geometry and in vivo robotic assisted minimally invasive surgery (MIS) image sequences.

Algorithms↗

PubMed2005

A practical approach towards accurate dense 3D depth recovery for robotic laparoscopic surgery.

OBJECTIVE: Recovering tissue deformation during robotic-assisted minimally invasive surgery (MIS) is an important step towards motion compensation and stabilization. This article presents a practical strategy for dense 3D depth recovery and temporal motion tracking for deformable surfaces. METHODS: The method combines image rectification with constrained disparity registration for reliable depth estimation. The accuracy and practical value of the technique are validated using a tissue phantom with known 3D geometry and motion characteristics and in vivo data. RESULTS: Results from the phantom model correctly follow the motion trend indicated from the ground truth provided by CT scanning, and regression analysis shows the intrinsic accuracy that can be achieved with the proposed technique. Results applied to in vivo robotic-assisted MIS data are also provided, indicating the practical value of the proposed method. CONCLUSION: The proposed method presents a practical strategy for dense depth recovery of surface structure in robotic-assisted MIS that incorporates stereo vision. Results on phantom and in vivo data indicate the quality of the method and also highlight the importance of further considering the effects of specular highlights.

Algorithms↗