Introducing Augmented Reality to Optical Coherence Tomography in Ophthalmic Microsurgery

Roodaki, Hessam; Filippatos, Konstantinos; Eslami, Abouzar; Navab, Nassir

doi:10.1109/ismar.2015.15

Cited by 19 publications

(18 citation statements)

References 17 publications

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“…2. Based on the algorithm from our previous work [18], [19], needle fragment can be robustly segmented in each B-scan image with dissolution of noise influence, see Fig. 3(a).…”

Section: Methods a The Framework For Proposed Methodsmentioning

confidence: 99%

Beveled needle position and pose estimation based on optical coherence tomography in ophthalmic microsurgery

Zhou

Huang

Eslami

et al. 2017

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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The needle position and pose is essential information in ophthalmic microsurgery. Estimation of these parameters is still an open problem, which hinders the application of various robot-assisted surgeries, such as autonomous injection. This paper presents a method to estimate the position and pose of beveled needle using three-dimensional Optical Coherence Tomography (OCT) image cube. The incomplete 3D point cloud of beveled needle obtained from OCT image cube is used to reconstruct the needle by fitting the projection of needle points based on its geometric features. We demonstrate the applicability of our method in ophthalmic injection surgery using ex vivo pig eyes and evaluate the accuracy of position and pose information using a micromanipulator.

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“…2. Based on the algorithm from our previous work [18], [19], needle fragment can be robustly segmented in each B-scan image with dissolution of noise influence, see Fig. 3(a).…”

Section: Methods a The Framework For Proposed Methodsmentioning

confidence: 99%

Beveled needle position and pose estimation based on optical coherence tomography in ophthalmic microsurgery

Zhou

Huang

Eslami

et al. 2017

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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“…4(a)) is transformed into a binary image by the thresholding method. The threshold value is adaptively defined, based on the statistical measurements of each B-scan [31]. We eliminate the noise inside the binary image, by applying a median filter followed by a Gaussian filter.…”

Section: B Needle Tip Localizationmentioning

confidence: 99%

Towards Robotic Eye Surgery: Marker-Free, Online Hand-Eye Calibration Using Optical Coherence Tomography Images

Zhou

Hamad

Weiß

et al. 2018

IEEE Robot. Autom. Lett.

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Ophthalmic microsurgery is known to be a challenging operation, which requires very precise and dexterous manipulation. Image guided robot-assisted surgery (RAS) 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 work, we developed a flexible framework for hand-eye calibration of an ophthalmic robot with a microscope-integrated Optical Coherence Tomography (MI-OCT) without any markers. The proposed method consists of three main steps: a) we estimate the OCT calibration parameters; b) with micro-scale displacements controlled by the robot, we detect and segment the needle tip in 3D-OCT volume; c) 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.

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“…A recent work of Roodaki et al [1] proposed to estimate the instrument tip depth to retina surface by building their method on top of instrument tracking algorithms. Despite of the high accuracy of the estimated depth, the algorithm relies on manual positioning of OCT scans or tracking algorithms which are prone to fail under high appearance changes.…”

Section: Previous Workmentioning

confidence: 99%

“…An efficient feedback of the distance between the instrument tip and the retina would minimize tissue damage caused by unintentional touch of retina. Recently, ophthalmic surgical microscopes are equipped with intraoperative Optical Coherence Tomography (OCT), which has been used in [1] to estimate the distance of the instrument to the retinal surface. However, continuous real-time detection of the instrument tip and instrument orientation is still required to enable automatic repositioning of the OCT scans during live surgery.…”

Section: Introductionmentioning

confidence: 99%

CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery

Alsheakhali

Eslami

Roodaki

et al. 2016

Computational and Mathematical Methods in Medicine

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Detection of instrument tip in retinal microsurgery videos is extremely challenging due to rapid motion, illumination changes, the cluttered background, and the deformable shape of the instrument. For the same reason, frequent failures in tracking add the overhead of reinitialization of the tracking. In this work, a new method is proposed to localize not only the instrument center point but also its tips and orientation without the need of manual reinitialization. Our approach models the instrument as a Conditional Random Field (CRF) where each part of the instrument is detected separately. The relations between these parts are modeled to capture the translation, rotation, and the scale changes of the instrument. The tracking is done via separate detection of instrument parts and evaluation of confidence via the modeled dependence functions. In case of low confidence feedback an automatic recovery process is performed. The algorithm is evaluated on in vivo ophthalmic surgery datasets and its performance is comparable to the state-of-the-art methods with the advantage that no manual reinitialization is needed.

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Introducing Augmented Reality to Optical Coherence Tomography in Ophthalmic Microsurgery

Cited by 19 publications

References 17 publications

Beveled needle position and pose estimation based on optical coherence tomography in ophthalmic microsurgery

Beveled needle position and pose estimation based on optical coherence tomography in ophthalmic microsurgery

Towards Robotic Eye Surgery: Marker-Free, Online Hand-Eye Calibration Using Optical Coherence Tomography Images

CRF-Based Model for Instrument Detection and Pose Estimation in Retinal Microsurgery

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