Robert Rohling

Rapid calibration for 3-D freehand ultrasound

3-D freehand ultrasound is a new imaging technique that is rapidly finding clinical applications. A position-sensing device is attached to a conventional ultrasound probe so that, as B-scans are acquired, they can be labelled with their relative positions and orientations. This allows a 3-D data set to be constructed from the B-scans. A key requirement of all freehand imaging systems is calibration; that is, determining the position and orientation of the B-scan with respect to the position sensor. This is typically a lengthy and tedious process that may need repeating every time a sensor is mounted on a probe. This paper describes a new calibration technique that takes only a few minutes to perform and produces results that compare favourably (in terms of both accuracy and precision) with previously published alternatives.

Hand-held steerable needle device

Minimally invasive percutaneous medical procedures are widely accepted in current clinical practice. However, with current techniques, the procedures are challenging and a high level of expertise is required to perform them successfully. This paper presents a novel steerable needle device for percutaneous interventions that allows the physician to steer the tip of the needle during insertion which eases the challenge associated with reaching the target. The steering concept uses slightly modified, off-the-shelf medical biopsy needles. A controlled lateral steering motion of over 30 mm during a 100-mm needle insertion is demonstrated with a 20-gauge needle in tissue-mimicking phantoms. A hand-held, motorized device has been built that actuates the needle base to produce a desired steering direction and magnitude at the tip. Steering commands may be supplied either by user input or by computer control. For the latter case, a method of software path planning has been developed that automatically steers the needle to a target.

Three-dimensional spatial compounding of ultrasound images.

One of the most promising applications of 3-D ultrasound lies in the visualization and volume estimation of internal 3-D structures. Unfortunately, the quality of the ultrasound data can be severely degraded by artefacts and speckle, making automatic analysis of the 3-D data sets very difficult. In this paper we investigate the use of 3-D spatial compounding to reduce speckle. We develop a new statistical theory to predict the improvement in signal-to-noise ratio with increased levels of compounding, and verify the predictions empirically. We also investigate how registration errors can affect automatic volume estimation of structures within the compounded 3-D data set. Having established the need to correct these errors, we present a novel reconstruction algorithm which uses landmarks to register each B-scan accurately as it is inserted into the voxel array. In a series of in vitro and in vivo trials, we demonstrate that 3-D spatial compounding is very effective for improving the signal-to-noise ratio, but correction of registration errors is essential.

A comparison of freehand three-dimensional ultrasound reconstruction techniques

Three-dimensional freehand ultrasound imaging produces a set of irregularly spaced B-scans, which are typically reconstructed on a regular grid for visualization and data analysis. Most standard reconstruction algorithms are designed to minimize computational requirements and do not exploit the underlying shape of the data. We investigate whether an approximation with splines holds any promise as a better reconstruction method. A radial basis function approximation method is implemented and compared with three standard methods. While the radial basis approach is computationally expensive, it produces accurate reconstructions without the kind of visible artefacts common with the standard methods. The other potential advantages of radial basis functions, such as the direct computation of derivatives, make further investigation worthwhile.

Automatic registration of 3-D ultrasound images

One of the most promising applications of 3-D ultrasound (US) lies in the visualisation and volume estimation of internal 3-D structures. Unfortunately, artifacts and speckle make automatic analysis of the 3-D data sets difficult. In this study, we investigated the use of 3-D spatial compounding to improve data quality, and found that precise registration is the key. A correlation-based registration technique was applied to 3-D ultrasound data sets acquired from in vivo examinations of a human gall bladder. We found that the registration technique performed well, and visualisation and segmentation of the compounded data were clearly improved. We also demonstrated that an automatic volume estimate made from the compounded data (13.0 mL) was comparable to a labour-intensive manual estimate (12.5 mL). In comparison, automatic estimates of uncompounded data are less accurate (ranging from 13.5 mL to 16.7 mL). The registration technique also has applications in intra- and interpatient comparative studies.

Bone Surface Localization in Ultrasound Using Image Phase-Based Features

Current practice in orthopedic surgery relies on intraoperative fluoroscopy as the main imaging modality for localization and visualization of bone tissue, fractures, implants and surgical tool positions. Ultrasound (US) has recently emerged as a potential nonionizing imaging alternative that promises safer operation while remaining relatively cheap and widely available. US images, however, often depict bone structures poorly, making automatic, accurate and robust localization of bone surfaces quite challenging. In this paper, we present a novel technique for automatic bone surface localization in US that uses local phase image information to derive symmetry-based features corresponding to tissue/bone interfaces through the use of 2-D Log-Gabor filters. We validate the performance of the proposed approach quantitatively using realistic phantom and in vitro experiments as well as qualitatively on in vivo data. Results demonstrate that the proposed technique detects bone surfaces with a localization mean error below 0.40 mm. Furthermore, small gaps between bone fragments can be detected with fracture displacement mean error below 0.33 mm for vertical misalignments, and 0.47 mm for horizontal misalignments.

Lumbar Spine Segmentation Using a Statistical Multi-Vertebrae Anatomical Shape+Pose Model

Segmentation of the spinal column from computed tomography (CT) images is a preprocessing step for a range of image-guided interventions. One intervention that would benefit from accurate segmentation is spinal needle injection. Previous spinal segmentation techniques have primarily focused on identification and separate segmentation of each vertebra. Recently, statistical multi-object shape models have been introduced to extract common statistical characteristics between several anatomies. These models can be used for segmentation purposes because they are robust, accurate, and computationally tractable. In this paper, we develop a statistical multi-vertebrae shape+pose model and propose a novel registration-based technique to segment the CT images of spine. The multi-vertebrae statistical model captures the variations in shape and pose simultaneously, which reduces the number of registration parameters. We validate our technique in terms of accuracy and robustness of multi-vertebrae segmentation of CT images acquired from lumbar vertebrae of 32 subjects. The mean error of the proposed technique is below 2 mm, which is sufficient for many spinal needle injection procedures, such as facet joint injections.

Methods for segmenting curved needles in ultrasound images

Ultrasound-guided percutaneous needle insertions are widely used techniques in current clinical practice. Some of these procedures have a high degree of difficulty because of poor observability of the needle in the ultrasound image. There have been recent efforts to improve guidance by computer assisted needle detection. These software techniques are often limited by not representing needle curvature. We present two methods to detect the needle in 2D ultrasound that specifically address needle curvature. Firstly, we demonstrate a real-time needle segmentation algorithm based on the Hough transform which detects the needle and represents its curved shape. Secondly, we demonstrate how a new coordinate transformation can transform detection of a curved needle to a linear fit. These methods are demonstrated on ultrasound and photographic images.

Hand-Held Steerable Needle Device

Minimally invasive percutaneous medical procedures are widely accepted in current clinical practice. However, with current techniques, the procedures are challenging and a high level of expertise is required to perform them successfully. This paper presents a novel steerable needle device for percutaneous interventions that allows the physician to steer the tip of the needle during insertion which eases the challenge associated with reaching the target. The steering concept uses slightly modified, off-the-shelf medical biopsy needles. A controlled lateral steering motion of over 30 mm during a 100-mm needle insertion is demonstrated with a 20-gauge needle in tissue-mimicking phantoms. A hand-held, motorized device has been built that actuates the needle base to produce a desired steering direction and magnitude at the tip. Steering commands may be supplied either by user input or by computer control. For the latter case, a method of software path planning has been developed that automatically steers the needle to a target.

3D needle-tissue interaction simulation for prostate brachytherapy

This paper presents a needle-tissue interaction model that is a 3D extension of a prior work based on the finite element method. The model is also adapted to accommodate arbitrary meshes so that the anatomy can effectively be meshed using third-party algorithms. Using this model a prostate brachytherapy simulator is designed to help medical residents acquire needle steering skills. This simulation uses a prostate mesh generated from clinical data segmented as contours on parallel slices. Node repositioning and addition, which are methods for achieving needle-tissue coupling, are discussed. In order to achieve realtime haptic rates, computational approaches to these methods are compared. Specifically, the benefit of using the Woodbury formula (matrix inversion lemma) is studied. Our simulation of needle insertion into a prostate is shown to run faster than 1 kHz.