Real-time three-dimensional flexible needle tracking using two-dimensional ultrasound

Vrooijink, Gustaaf J.; Abayazid, Momen; Misra, Sarthak

doi:10.1109/icra.2013.6630797

Cited by 68 publications

(81 citation statements)

References 26 publications

(7 reference statements)

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“…This teslameter is able to measure the field components with a resolution of 0.1 mT. In the validation procedure the Hall probe is swept through the entire workspace by an XYZ Cartesian robot at constant velocity of 0.5 mm/sec [34], [35]. The validation is performed on 1523 samples in the 1.2×1.2 cm workspace for a resulting sampling rate of 6.8×10 6 samples/m 2 .…”

Section: ) Magnetic Fields Validationmentioning

confidence: 99%

Evaluation of an electromagnetic system with haptic feedback for control of untethered, soft grippers affected by disturbances

Ongaro

Pacchierotti

Yoon

et al. 2016

2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)

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Abstract-Current wireless, small-scale robots have restricted manipulation capabilities, and limited intuitive tools to control their motion. This paper presents a novel teleoperation system with haptic feedback for the control of untethered soft grippers. The system is able to move and open/close the grippers by regulating the magnetic field and temperature in the workspace. Users can intuitively control the grippers using a grounded haptic interface, that is also capable of providing compelling force feedback information as the gripper interacts with the environment. The magnetic closed-loop control algorithm is designed starting from a Finite Element Model analysis. The electromagnetic model used is validated by a measurement of the magnetic field with a resolution of 0.1 mT and sampling rate of 6.8×10 6 samples/m 2 . The system shows an accuracy in positioning the gripper of 0.08 mm at a velocity of 0.81 mm/s. The robustness of the control and tracking algorithms are tested by spraying the workspace with water drops that cause glares and related disturbances of up to 0.41 mm.

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Section: ) Magnetic Fields Validationmentioning

confidence: 99%

Evaluation of an electromagnetic system with haptic feedback for control of untethered, soft grippers affected by disturbances

Ongaro

Pacchierotti

Yoon

et al. 2016

2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)

Self Cite

View full text Add to dashboard Cite

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“…Nevertheless, due to the limitation of two-dimensional (2D) microscopic images, these detection results in en-face plane view cannot provide enough information to locate the needle pose and position in three-dimensional (3D) space. Many widely used 3D medical imaging technologies, such as computed tomography (CT) scans, fluoroscopy, magnetic resonance (MR) and ultrasound are already applied in brain, thoracic and cardiac surgeries, not only for diagnostic procedures but also as real-time surgical guides [9][10][11][12][13]. However, these imaging modalities cannot achieve a sufficient resolution for ophthalmic interventions.…”

Section: Introductionmentioning

confidence: 99%

Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery

et al. 2017

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Needle segmentation is a fundamental step for needle reconstruction and image-guided surgery. Although there has been success stories in needle segmentation for non-microsurgeries, the methods cannot be directly extended to ophthalmic surgery due to the challenges bounded to required spatial resolution. As the ophthalmic surgery is performed by finer and smaller surgical instruments in micro-structural anatomies, specifically in retinal domains, difficulties are raised for delicate operation and sensitive perception. To address these challenges, in this paper we investigate needle segmentation in ophthalmic operation on 60 Optical Coherence Tomography (OCT) cubes captured during needle injection surgeries on ex-vivo pig eyes. Furthermore, we developed two different approaches, a conventional method based on morphological features (MF) and a specifically designed full convolution neural networks (FCN) method, moreover, we evaluate them on the benchmark for needle segmentation in the volumetric OCT images. The experimental results show that FCN method has a better segmentation performance based on four evaluation metrics while MF method has a short inference time, which provides valuable reference for future works.

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“…Most studies use softtissue simulants made from homogeneous gelatin phantoms, in which the needle can be easily located from the ultrasound images. Vrooijink et al attached an ultrasound transducer to a Cartesian robot [12], [19]. They combined 2D ultrasound images with transducer position feedback to track the needle in 3D, both in gelatin phantoms and in biological tissue.…”

Section: Introductionmentioning

confidence: 99%

Steering an actuated-tip needle in biological tissue: Fusing FBG-sensor data and ultrasound images

Shahriari

Roesthuis

Berg

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Needle insertion procedures are commonly performed in current clinical practice for diagnostic and therapeutic purposes. Although prevailing technology allows accurate localization of lesions, they cannot yet be precisely targeted. Needle steering is a promising technique to overcome this challenge. In this paper, we describe the development of a novel steering system for an actuated-tip flexible needle. Strain measurements from an array of Fiber Bragg Grating (FBG) sensors are used for online reconstruction of the needle shape in 3D-space. FBG-sensor data is then fused with ultrasound images obtained from a clinically-approved Automated Breast Volume Scanner (ABVS) using an unscented Kalman filter. A new ultrasound-based tracking algorithm is developed for the robust tracking of the needle in biological tissue. Two experimental cases are presented to evaluate the proposed steering system. In the first case, the needle shape is reconstructed using the tracked tip position in ultrasound images and FBGsensor measurements, separately. The reconstructed shape is then compared with the actual 3D needle shape obtained from the ABVS. In the second case, two steering experiments are performed to evaluate the overall system by fusing the FBGsensor data and ultrasound images. Average targeting errors are 1.29±0.41 mm and 1.42±0.72 mm in gelatin phantom and biological tissue, respectively.

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Real-time three-dimensional flexible needle tracking using two-dimensional ultrasound

Cited by 68 publications

References 26 publications

Evaluation of an electromagnetic system with haptic feedback for control of untethered, soft grippers affected by disturbances

Evaluation of an electromagnetic system with haptic feedback for control of untethered, soft grippers affected by disturbances

Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery

Steering an actuated-tip needle in biological tissue: Fusing FBG-sensor data and ultrasound images

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