A new adaptive interpolation algorithm for 3D ultrasound imaging with speckle reduction and edge preservation

Author name used in this publication: Qinghua HuangAuthor name used in this publication: Yongping ZhengAuthor name used in this publication: Minhua Lu2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Development of a portable 3D ultrasound imaging system for musculoskeletal tissues

Author name used in this publication: Q. H. HuangAuthor name used in this publication: Y. P. ZhengAuthor name used in this publication: M. H. LuAuthor name used in this publication: Z. R. ChiCentre for Signal Processing, Department of Electronic and Information EngineeringRehabilitation Engineering Centre2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A Low-Cost Camera-based Transducer Tracking System for Freehand Three-Dimensional Ultrasound Imaging

Freehand three-dimensional ultrasound (3D US) imaging is commonly used for clinical diagnosis and therapy monitoring. In this technique, accurate tracking of the US transducer is a crucial requirement to develop high-quality 3D US volumes. However, current methods for transducer tracking are generally expensive and inconvenient. This thesis presents a low-cost camera-based system for tracking the US transducer with six degrees of freedom (DoF). In this system, two orthogonal cameras with non-overlapped views are mounted on the US transducer. During US scanning, the two cameras are employed to track artificial features attached to the skin of the patient. A 3D surface map is constructed based on the tracked features and the 3D poses of each camera with respect to the skin are extracted separately. The estimated poses of the two cameras are spatially combined to provide accurate and robust pose estimation of the US transducer. In particular, the fusion of the estimated poses by the two cameras is performed using Kalman filtering based technique, which is a popular optimization technique in motion guidance and tracking. The camera-based tracking of the US transducer has been applied to synthesize freehand 3D US volumes. The performance of the proposed system is evaluated by performing in-vitro 3D US imaging experiments and quantifying the synthesized US volumes. The results demonstrate that two points in the 3D US volume separated by a distance of 10 mm can be reconstructed with an average error of 0.35 mm and a 3D volume of a cylinder can be estimated within an error of 3.8%

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

Quantitative three-dimensional elasticity imaging from quasi-static deformation: a phantom study

We present a methodology to image and quantify the shear elastic modulus of three-dimensional (3D) breast tissue volumes held in compression under conditions similar to those of a clinical mammography system. Tissue phantoms are made to mimic the ultrasonic and mechanical properties of breast tissue. Stiff lesions are created in these phantoms with size and modulus contrast values, relative to the background, that are within the range of values of clinical interest. A two-dimensional ultrasound system, scanned elevationally, is used to acquire 3D images of these phantoms as they are held in compression. From two 3D ultrasound images, acquired at different compressed states, a three-dimensional displacement vector field is measured. The measured displacement field is then used to solve an inverse problem, assuming the phantom material to be an incompressible, linear elastic solid, to recover the shear modulus distribution within the imaged volume. The reconstructed values are then compared to values measured independently by direct mechanical testing.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65094/2/pmb9_3_019.pd

Ultrasound-Augmented Laparoscopy

Laparoscopic surgery is perhaps the most common minimally invasive procedure for many diseases in the abdomen. Since the laparoscopic camera provides only the surface view of the internal organs, in many procedures, surgeons use laparoscopic ultrasound (LUS) to visualize deep-seated surgical targets. Conventionally, the 2D LUS image is visualized in a display spatially separate from that displays the laparoscopic video. Therefore, reasoning about the geometry of hidden targets requires mentally solving the spatial alignment, and resolving the modality differences, which is cognitively very challenging. Moreover, the mental representation of hidden targets in space acquired through such cognitive medication may be error prone, and cause incorrect actions to be performed. To remedy this, advanced visualization strategies are required where the US information is visualized in the context of the laparoscopic video. To this end, efficient computational methods are required to accurately align the US image coordinate system with that centred in the camera, and to render the registered image information in the context of the camera such that surgeons perceive the geometry of hidden targets accurately. In this thesis, such a visualization pipeline is described. A novel method to register US images with a camera centric coordinate system is detailed with an experimental investigation into its accuracy bounds. An improved method to blend US information with the surface view is also presented with an experimental investigation into the accuracy of perception of the target locations in space

Freehand three dimensional ultrasound for imaging components of the musculoskeletal system

There have been reports on the use of Ultrasound (US) for monitoring fracture repair and for measuring muscle volume. Change in muscle mass is a useful bio-marker for monitoring the use and disuse of muscle, and the affects of age, disease and injury. The main modality for imaging bone is X-ray and for muscle volume Magnetic Resonance (MR). Previous studies have shown US to have advantages over X-ray and MR. US can image all stages of the fracture repair process and can detect signs of healing 4-6 weeks before X-ray allowing earlier detection of possible complications. Compared to MR, US is less resource intensive, easier to access and also has fewer exclusion criteria for patients. Despite these advantages, the limited field of view that US can provide results in high operator dependency for scan interpretation and also for length and volume measurements. Three-dimensional Ultrasound (3D US) has been developed to overcome these limitations and has been used to provide extended field of view images of the foetus and the heart and to obtain accurate volume measurements for organs. In this thesis it is hypothesized that 3D US can provide a more comprehensive method of imaging fracture repair than X-ray and is also a viable alternative to MR for determining muscle volumes in vivo. Initially, an electromagnetically (EM) tracked 3D US system was evaluated for clinical use using phantom-based experiments. It was found that the presence of metal objects in or near the EM field caused distortion and resulted in errors in the volume measurements of phantoms of up to ±20%. An optically tracked system was also evaluated and it was found that length measurements of a phantom could be made to within ±1.3%. Fracture repair was monitored in five patients with lower limb fractures. Signs of healing were visible earlier on 3D US with a notable, although variable, lag between callus development on X-ray compared to 3D US. 3D US provided a clearer view of callus formation and the changes in density of the callus as it matured. Additional information gained by applying image processing methods to the 3D US data was used to develop a measure of callus density and to identify the frequency dependent appearance of the callus. Volume measurements of the rectus femoris quadricep muscle were obtained using 3DUS from eleven healthy volunteers and were validated against volume measurements derived using MR. The mean difference between muscle volume measurements obtained using 3D US and MR was 0.53 cm3 with a standard deviation of 1.09 cm3 and 95% confidence intervals of 0.20 - 1.27 cm3 In conclusion, 3D US demonstrates great potential as a tool for imaging components of the musculoskeletal system and as means of measuring callus density

Neurosurgical Ultrasound Pose Estimation Using Image-Based Registration and Sensor Fusion - A Feasibility Study

Modern neurosurgical procedures often rely on computer-assisted real-time guidance using multiple medical imaging modalities. State-of-the-art commercial products enable the fusion of pre-operative with intra-operative images (e.g., magnetic resonance [MR] with ultrasound [US] images), as well as the on-screen visualization of procedures in progress. In so doing, US images can be employed as a template to which pre-operative images can be registered, to correct for anatomical changes, to provide live-image feedback, and consequently to improve confidence when making resection margin decisions near eloquent regions during tumour surgery. In spite of the potential for tracked ultrasound to improve many neurosurgical procedures, it is not widely used. State-of-the-art systems are handicapped by optical tracking’s need for consistent line-of-sight, keeping tracked rigid bodies clean and rigidly fixed, and requiring a calibration workflow. The goal of this work is to improve the value offered by co-registered ultrasound images without the workflow drawbacks of conventional systems. The novel work in this thesis includes: the exploration and development of a GPU-enabled 2D-3D multi-modal registration algorithm based on the existing LC2 metric; and the use of this registration algorithm in the context of a sensor and image-fusion algorithm. The work presented here is a motivating step in a vision towards a heterogeneous tracking framework for image-guided interventions where the knowledge from intraoperative imaging, pre-operative imaging, and (potentially disjoint) wireless sensors in the surgical field are seamlessly integrated for the benefit of the surgeon. The technology described in this thesis, inspired by advances in robot localization demonstrate how inaccurate pose data from disjoint sources can produce a localization system greater than the sum of its parts

Medical image analysis methods for anatomical surface reconstruction using tracked 3D ultrasound

The thesis focuses on a study of techniques for acquisition and reconstruction of surface data from anatomical objects by means of tracked 3D ultrasound. In the context of the work two experimental scanning systems are developed and tested on both artificial objects and biological tissues. The first system is based on the freehand ultrasound principle and utilizes a conventional 2D ultrasound transducer coupled with an electromechanical 3D position tracker. The main properties and the basic features of this system are discussed. A number of experiments show that its accuracy in the close to ideal conditions reaches 1.2 mm RMS. The second proposed system implements the sequential triggered scanning approach. The system consists of an ultrasound machine, a workstation and a scanning body (a moving tank filled with liquid and a transducer fixation block) that performs transducer positioning and tracking functions. The system is tested on artificial and real bones. The performed experiments illustrate that it provides significantly better accuracy than the freehand ultrasound (about 0.2 mm RMS) and allows acquiring regular data with a good precision. This makes such a system a promising tool for orthopaedic and trauma surgeons during contactless X-ray-free examinations of injured extremities. The second major subject of the thesis concerns development of medical image analysis methods for 3D surface reconstruction and 2D object detection. We introduce a method based on mesh-growing surface reconstruction that is designed for noisy and sparse data received from 3D tracked ultrasound scanners. A series of experiments on synthetic and ultrasound data show an appropriate reconstruction accuracy. The reconstruction error is measured as the averaged distance between the faces of the mesh and the points from the cloud. Dependently on the initial settings of the method the error varies in range 0.04 - 0.2% for artificial data and 0.3 - 0.7 mm for ultrasound bone data. The reconstructed surfaces correctly interpolate the original point clouds and demonstrate proper smoothness. The next significant problem considered in the work is 2D object detection. Although medical object detection is not integrated into the developed scanning systems, it can be used as a possible further extension of the systems for automatic detection of specific anatomical structures. We analyse the existent object detection methods and introduce a modification of the one based on the popular Generalized Hough Transform (GHT). Unlike the original GHT, the developed method is invariant to rotation and uniform scaling, and uses an intuitive two-point parametrization. We propose several implementations of the feature-to-vote conversion function with the corresponding vote analysis principles. Special attention is devoted to a study of the hierarchical vote analysis and its probabilistic properties. We introduce a parameter space subdivision strategy that reduces the probability of vote peak omission, and show that it can be efficiently implemented in practice using the Gumbel probability distribution