Ophthalmic microsurgery is known to be a challenging operation, which requires very precise and dexterous manipulation. Image guided robot-assisted surgery is a promising solution that brings significant improvements in outcomes and reduces the physical limitations of human surgeons. However, this technology must be further developed before it can be routinely used in clinics. One of the problems is the lack of proper calibration between the robotic manipulator and appropriate imaging device. In this letter, we developed a flexible framework for hand-eye calibration of an ophthalmic robot with a microscope-integrated optical coherence tomography (OCT) without any markers. The proposed method consists of three main steps are following: First, we estimate the OCT calibration parameters; second, with micro-scale displacements controlled by the robot, we detect and segment the needle tip in three-dimensional OCT volume and; finally, we find the transformation between the coordinate system of the OCT camera and the coordinate system of the robot. We verified the capability of our framework in ex-vivo pig eye experiments and compared the results with a reference method (marker-based). In all experiments, our method showed a small difference from the marker based method, with a mean calibration error of 9.2 μm and 7.0 μm, respectively. Additionally, the noise test shows the robustness of the proposed method.
In the surgical environment, hand-eye calibration is normally transferred into a Procrustean problem by the @cite_11 and has been modified to meet with different surgical requirements in various 3D medical imaging scenarios, e.g. two-camera stereoscopic vision and ultrasound. To determine the unknown fixed transformation between the robot and imaging coordinates, a ball-tip stylus or chessboard is used as a calibrator for hand-eye calibration @cite_27 . However, these markers may influence the conventional surgical workflow as well as cause complication with sterility. @cite_7 designed a tracking collar for rigid laparoscopes hand-eye calibration. The method can achieve 0.85 mm error, and the calibration process can be finished within 3 minutes. In another work, 3D markers were used by @cite_21 to realize ultrasound probe calibration with a robotic arm. In terms of none marker research work, @cite_15 used ultrasound volume registration data to achieve calibration that does not require 3D localizers. @cite_2 proposed a calibration method where an instrument with known geometry is used instead of an additional calibrator. The calibration was achieved without compromising sterility. @cite_3 @cite_20 used constraints based on the needle orientation in 2D 3D ultrasound image to calibrate the ultrasound probe.
@cite_7 @cite_21 @cite_3 @cite_27 @cite_2 @cite_15 @cite_20 @cite_11
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3D UltraSound (US) probes are used in clinical applications for their ease of use and ability to obtain intra-operative volumes. In surgical navigation applications a calibration step is needed to localize the probe in a general coordinate system. This paper presents a new hand-eye calibration method using directly the kinematic model of a robot and US volume registration data that does not require any 3D localizers. First results show a targeting error of 2.34 mm on an experimental setup using manual segmentation of five beads in ten US volumes. In a robot mounted camera arrangement, hand-eye calibration estimates the rigid relationship between the robot and camera coordinate frames. Most hand-eye calibration techniques use a calibration object to estimate the relative transformation of the camera in several views of the calibration object and link these to the forward kinematics of the robot to compute the hand-eye transformation. Such approaches achieve good accuracy for general use but for applications such as robotic assisted minimally invasive surgery, acquiring a calibration sequence multiple times during a procedure is not practical. In this paper, we present a new approach to tackle the problem by using the robotic surgical instruments as the calibration object with well known geometry from CAD models used for manufacturing. Our approach removes the requirement of a custom sterile calibration object to be used in the operating room and it simplifies the process of acquiring calibration data when the laparoscope is constrained to move around a remote centre of motion. This is the first demonstration of the feasibility to perform hand-eye calibration using components of the robotic system itself and we show promising validation results on synthetic data as well as data acquired with the da Vinci Research Kit. We propose a minimal solution for the similarity registration (rigid pose and scale) between two sets of 3D lines, and also between a set of co-planar points and a set of 3D lines. The first problem is solved up to 8 discrete solutions with a minimum of 2 line-line correspondences, while the second is solved up to 4 discrete solutions using 4 point-line correspondences. We use these algorithms to perform the extrinsic calibration between a pose tracking sensor and a 2D 3D ultrasound (US) curvilinear probe using a tracked needle as calibration target. The needle is tracked as a 3D line, and is scanned by the ultrasound as either a 3D line (3D US) or as a 2D point (2D US). Since the scale factor that converts US scan units to metric coordinates is unknown, the calibration is formulated as a similarity registration problem. We present results with both synthetic and real data and show that the minimum solutions outperform the correspondent non-minimal linear formulations. In this study, we registered live-time interventional magnetic resonance imaging (iMRI) slices with a previously obtained high-resolution MRI volume that in turn can be registered with a variety of functional images, e.g., PET, SPECT, for tumor targeting. We created and evaluated a slice-to-volume (SV) registration algorithm with special features for its potential use in iMRI-guided radio-frequency (RF) thermal ablation of prostate cancer. The algorithm features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. Imaging experiments were performed on volunteers using a conventional 1.5-T MR scanner and a clinical 0.2-T C-arm iMRI system under realistic conditions. Both high-resolution MR volumes and actual iMRI image slices were acquired from the same volunteers. Actual and simulated iMRI images were used to test the dependence of SV registration on image noise, receive coil inhomogeneity, and RF needle artifacts. To quantitatively assess registration, we calculated the mean voxel displacement over a volume of interest between SV registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed. For transverse image slices covering the prostate, the SV registration algorithm was 100 successful with an error of <2 mm, and the average and standard deviation was only 0.4 mm spl plusmn 0.2 mm. Visualizations such as combined sector display and contour overlay showed excellent registration of the prostate and other organs throughout the pelvis. Error was greater when an image slice was obtained at other orientations and positions, mostly because of inconsistent image content such as that from variable rectal and bladder filling. These preliminary experiments indicate that MR SV registration is sufficiently accurate to aid image-guided therapy.