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3D Ultrasound

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Graham M. Treece – One of the best experts on this subject based on the ideXlab platform.

  • Particle swarm optimization for in vivo 3D Ultrasound volume registration
    Acoustical Imaging, 2011
    Co-Authors: Umer Zeeshan Ijaz, Andrew H. Gee, Richard W. Prager, Graham M. Treece

    Abstract:

    As three-dimensional (3D) Ultrasound is becoming more and more popular, there has been increased interest in using a position sensor to track the trajectory of the 3D Ultrasound probe during the scan. One application is the improvement of image quality by fusion of multiple scans from different orientations. With a position sensor mounted on the probe, the clinicians face additional difficulties, for example, maintaining a line-of-sight between the sensor and the reference point. Therefore, the objective of this paper is to register the volumes using an automatic image-based registration technique. In this paper, we employ the particle swarm optimization (PSO) technique to calculate the six rigid-body transformation parameters (three for translation and three for rotation) between successive volumes of 3D Ultrasound data. We obtain vertical and horizontal slices through the acquired volumes and then use an intensity-based similarity measure as a fitness function for each particle. We considered various settings in the PSO to find a set of parameters to give the best convergence. We found the visually acceptable registration when the initial orientations of the particles were confined to within a few degrees of the orientations obtained from position sensor.

  • A Study of Similarity Measures for In Vivo 3D Ultrasound Volume Registration
    Acoustical Imaging, 2011
    Co-Authors: Umer Zeeshan Ijaz, Andrew H. Gee, Richard W. Prager, Graham M. Treece

    Abstract:

    Most of the conventional Ultrasound machines in hospitals work in two dimensions. However, there are some applications where doctors would like to be able to gather Ultrasound data as a three-dimensional (3D) block rather than a two-dimensional (2D) slice. Two different types of 3D Ultrasound have been developed to meet this requirement. One type involves a special probe that can record a fixed block of data, either by having an internal sweeping mechanism or by using electronic steering. The other type of 3D Ultrasound uses a conventional 2D Ultrasound probe together with a position sensor and is called freehand 3D Ultrasound. A natural progression of the mechanically-swept 3D Ultrasound system is to combine it with the free hand sensor. This results in an extended field of view. There are two major problems with using a position sensor. Firstly, line-of-sight needs to be maintained between the sensor and the reference point. Secondly, the multiple volumes rarely register because of tissue displacement and deformation. Therefore, the objective of this paper is to get rid of the inconvenient position sensor and to use an automatic image-based registration technique. We provide an experimental study of several intensity-based similarity measures for the registration of 3D Ultrasound volumes. Rather than choosing a conventional voxel array to represent the 3D blocks, we use corresponding vertical and horizontal image slices from the blocks to be matched. This limits the amount of data thus making the calculation of the similarity measure less computationally expensive.

  • RF and amplitude-based probe pressure correction for 3D Ultrasound.
    Ultrasound in Medicine & Biology, 2005
    Co-Authors: Graham M. Treece, Andrew H. Gee, Richard W. Prager

    Abstract:

    Anatomical deformation caused by variable probe contact pressure is a significant problem in freehand 3D Ultrasound, particularly for high resolution musculoskeletal and breast scans. We have previously published an amplitude-based algorithm for correcting such errors. In this paper, we compare this approach with a novel, elastography-inspired algorithm which works with the higher resolution radio-frequency (RF) signal. The results show that, although the RF-based algorithm is more precise in certain circumstances, both algorithms are able to compensate for probe pressure in 3D Ultrasound data. Consequently, freehand 3D Ultrasound users who do not have access to the RF signal are still in a position to perform effective probe pressure correction using the readily available video output, as long as this signal is not affected by significant amounts of frame averaging (persistence).

Jocelyne Troccaz – One of the best experts on this subject based on the ideXlab platform.

  • Efficient target tracking for 3D Ultrasound-guided needle steering
    , 2020
    Co-Authors: Guillaume Lapouge, Philippe Poignet, Gaelle Fiard, Jocelyne Troccaz

    Abstract:

    3D Ultrasound imaging can be used in the context of robotic needle steering to reach a physical target with a flexible, steerable needle. During the insertion, the tissue may be deformed by the inserted needle, patient breathing or external force application. It may therefore be necessary to track intra-operatively the displacement of the target. Most Ultrasound based needle steering works concentrate on 2D Ultrasound probes [1], [2], [3] which do not allow to simultaneously track both the target and the needle during 3D needle steering. Physical target tracking in 3D Ultrasound-guided needle steering is seldom carried out [4][5], and may require computational power that is precious for intra-operative needle steering. This paper proposes a new approach for computationally inexpensive and precise tracking of a moving target in 3D B-mode Ultrasound volumes. It is based on the interconnection of intensity-based tracking and motion estimation algorithms. The intensity-based tracking consists in a 3D extension of the Diamond Shape block matching algorithm, used here for the first time in 3D Ultrasound volumes for tissue tracking. The motion estimation is done by linear Kalman filtering. It predicts the next target position and ensures faster and more robust convergence of the Diamond Shape block matching algorithm. An experimental validation on ex-vivo tissue is proposed with promising tracking precision (estimated average error of 0.3mm) while significantly lowering the computational cost when compared to classical block matching based tracking.

  • Needle localization for needle steering under 3D Ultrasound feedback
    , 2018
    Co-Authors: Guillaume Lapouge, Jocelyne Troccaz, Philippe Poignet

    Abstract:

    In needle steering, estimating the needle pose is a critical problem. In 3D Ultrasound volumes, fine needle localization is difficult and requires a combination of estimation and image processing to be successful. Indeed, 3D Ultrasound imaging suffers from noise, artifacts and works at a low frequency. We propose a needle tip pose estimation method in the context of 3D robotic needle steering under 3D Ultrasound feedback, based on multi-rate, multi-sensor fusion [1].

  • A 3D Ultrasound Robotic Prostate Brachytherapy System with Prostate Motion Tracking
    IEEE Transactions on Robotics, 2012
    Co-Authors: Nikolai Hungr, Michael Baumann, Jean-alexandre Long, Jocelyne Troccaz

    Abstract:

    This paper describes a new three-dimensional (3D) Ultrasound robotic prostate brachytherapy system. It uses a stationary 3D Ultrasound probe rigidly fixed to a robotic needle insertion mechanism. The novelty of the system is its ability to track prostate motion intra-operatively to allow the dose planning and needle trajectories or depths to be adapted to take into account these motions. Prostate tracking is done using a fast 3D Ultrasound registration algorithm previously validated for biopsy guidance. The 7 degree of freedom robot and Ultrasound probe are calibrated together with an accuracy of 0.9mm, allowing the needles to be precisely inserted to the seed targets chosen in the reference Ultrasound image. Experiments were conducted on mobile deformable synthetic prostate phantoms, using a prototype laboratory system. Results showed that, with prostate motions of up to 7mm, the system was able to reach the chosen targets with less than 2mm accuracy in the needle insertion direction. This measured accuracy included extrinsic measurement errors of up to 1.1mm. A preliminary cadaver feasibility study was also described, in preparation for more realistic experimentation of the system.

Richard W. Prager – One of the best experts on this subject based on the ideXlab platform.

  • A Study of Similarity Measures for In Vivo 3D Ultrasound Volume Registration
    Acoustical Imaging, 2011
    Co-Authors: Umer Zeeshan Ijaz, Andrew H. Gee, Richard W. Prager, Graham M. Treece

    Abstract:

    Most of the conventional Ultrasound machines in hospitals work in two dimensions. However, there are some applications where doctors would like to be able to gather Ultrasound data as a three-dimensional (3D) block rather than a two-dimensional (2D) slice. Two different types of 3D Ultrasound have been developed to meet this requirement. One type involves a special probe that can record a fixed block of data, either by having an internal sweeping mechanism or by using electronic steering. The other type of 3D Ultrasound uses a conventional 2D Ultrasound probe together with a position sensor and is called freehand 3D Ultrasound. A natural progression of the mechanically-swept 3D Ultrasound system is to combine it with the free hand sensor. This results in an extended field of view. There are two major problems with using a position sensor. Firstly, line-of-sight needs to be maintained between the sensor and the reference point. Secondly, the multiple volumes rarely register because of tissue displacement and deformation. Therefore, the objective of this paper is to get rid of the inconvenient position sensor and to use an automatic image-based registration technique. We provide an experimental study of several intensity-based similarity measures for the registration of 3D Ultrasound volumes. Rather than choosing a conventional voxel array to represent the 3D blocks, we use corresponding vertical and horizontal image slices from the blocks to be matched. This limits the amount of data thus making the calculation of the similarity measure less computationally expensive.

  • Particle swarm optimization for in vivo 3D Ultrasound volume registration
    Acoustical Imaging, 2011
    Co-Authors: Umer Zeeshan Ijaz, Andrew H. Gee, Richard W. Prager, Graham M. Treece

    Abstract:

    As three-dimensional (3D) Ultrasound is becoming more and more popular, there has been increased interest in using a position sensor to track the trajectory of the 3D Ultrasound probe during the scan. One application is the improvement of image quality by fusion of multiple scans from different orientations. With a position sensor mounted on the probe, the clinicians face additional difficulties, for example, maintaining a line-of-sight between the sensor and the reference point. Therefore, the objective of this paper is to register the volumes using an automatic image-based registration technique. In this paper, we employ the particle swarm optimization (PSO) technique to calculate the six rigid-body transformation parameters (three for translation and three for rotation) between successive volumes of 3D Ultrasound data. We obtain vertical and horizontal slices through the acquired volumes and then use an intensity-based similarity measure as a fitness function for each particle. We considered various settings in the PSO to find a set of parameters to give the best convergence. We found the visually acceptable registration when the initial orientations of the particles were confined to within a few degrees of the orientations obtained from position sensor.

  • RF and amplitude-based probe pressure correction for 3D Ultrasound.
    Ultrasound in Medicine & Biology, 2005
    Co-Authors: Graham M. Treece, Andrew H. Gee, Richard W. Prager

    Abstract:

    Anatomical deformation caused by variable probe contact pressure is a significant problem in freehand 3D Ultrasound, particularly for high resolution musculoskeletal and breast scans. We have previously published an amplitude-based algorithm for correcting such errors. In this paper, we compare this approach with a novel, elastography-inspired algorithm which works with the higher resolution radio-frequency (RF) signal. The results show that, although the RF-based algorithm is more precise in certain circumstances, both algorithms are able to compensate for probe pressure in 3D Ultrasound data. Consequently, freehand 3D Ultrasound users who do not have access to the RF signal are still in a position to perform effective probe pressure correction using the readily available video output, as long as this signal is not affected by significant amounts of frame averaging (persistence).