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- Needle guidance using handheld stereo vision and projection for ultrasound-based interventions. [Journal Article]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):684-91.
With real-time instrument tracking and in-situ guidance projection directly integrated in a handheld ultrasound imaging probe, needle-based interventions such as biopsies become much simpler to perform than with conventionally-navigated systems. Stereo imaging with needle detection can be made sufficiently robust and accurate to serve as primary navigation input. We describe the low-cost, easy-to-use approach used in the Clear Guide ONE generic navigation accessory for ultrasound machines, outline different available guidance methods, and provide accuracy results from phantom trials.
- Automatic labelling of tumourous frames in free-hand laparoscopic ultrasound video. [Journal Article, Research Support, Non-U.S. Gov't]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):676-83.
Laparoscopic ultrasound (US) is often used during partial nephrectomy surgeries to identify tumour boundaries within the kidney. However, visual identification is challenging as tumour appearance varies across patients and US images exhibit significant noise levels. To address these challenges, we present the first fully automatic method for detecting the presence of kidney tumour in free-hand laparoscopic ultrasound sequences in near real-time. Our novel approach predicts the probability that a frame contains tumourous tissue using random forests and encodes this probability combined with a regularization term within a graph. Using Dijkstra's algorithm we find a globally optimal labelling (tumour vs. non-tumour) of each frame. We validate our method on a challenging clinical dataset composed of five patients, with a total of 2025 2D ultrasound frames, and demonstrate the ability to detect the presence of kidney tumour with a sensitivity and specificity of 0.774 and 0.916, respectively.
- Full-wave intravascular ultrasound simulation from histology. [Journal Article, Research Support, Non-U.S. Gov't]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):627-34.
In this paper, we introduce a framework for simulating intravascular ultrasound (IVUS) images and radiofrequency (RF) signals from histology image counterparts. We modeled the wave propagation through the Westervelt equation, which is solved explicitly with a finite differences scheme in polar coordinates by taking into account attenuation and non-linear effects. Our results demonstrate good correlation for textural and spectral information driven from simulated IVUS data in contrast to real data, acquired with single-element mechanically rotating 40 MHZ transducer, as ground truth.
- 3D velocity field and flow profile reconstruction from arbitrarily sampled Doppler ultrasound data. [Journal Article, Research Support, Non-U.S. Gov't]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):611-8.
With the need for adequate analysis of blood flow dynamics, different maging modalities have been developed to measure varying blood velocities over time. Due to its numerous advantages, Doppler ultrasound sonography remains one of the most widely used techniques in clinical routine, but requires additional preprocessing to recover 3D velocity information. Despite great progress in the last years, recent approaches do not jointly consider spatial and temporal variation in blood flow. In this work, we present a novel gating- and compounding-free method to simultaneously reconstruct a 3D velocity field and a temporal flow profile from arbitrarily sampled Doppler ultrasound measurements obtained from multiple directions. Based on a laminar flow assumption, a patch-wise B-spline formulation of blood velocity is coupled for the first time with a global waveform model acting as temporal regularization. We evaluated our method on three virtual phantom datasets, demonstrating robustness in terms of noise, angle between measurements and data sparsity, and applied it successfully to five real case datasets of carotid artery examination.
- Active echo: a new paradigm for ultrasound calibration. [Journal Article]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):397-404.
In ultrasound-guided medical procedures, accurate tracking of interventional tools with respect to the US probe is crucial to patient safety and clinical outcome. US probe tracking requires an unavoidable calibration procedure to recover the rigid body transformation between the US image and the tracking coordinate system. In literature, almost all calibration methods have been performed on passive phantoms. There are several challenges to these calibration methods including dependency on ultrasound image quality and parameters such as frequency, depth, and beam-thickness. In this work, for the first time we introduce an active echo (AE) phantom for US calibration. The phantom actively detects and responds to the US beams from the imaging probe. This active approach allows reliable and accurate identification of the ultrasound image mid-plane independent of the image quality. It also enables automatic point segmentations. Both the target localization and segmentation can be done automatically, so the user dependency is minimized. The AE phantom is compared with a gold standard crosswire (CW) phantom in a robotic US experimental setup. The result indicates that AE calibration phantom provides a localization precision of 223 μm, and an overall reconstruction error of 850 μm. Autosegmentation is also tested and proved to have the similar performance as the manual segmentation.
- A new sensor technology for 2D ultrasound-guided needle tracking. [Journal Article]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):389-96.
2D Ultrasound (US) is becoming the preferred modality for image-guided interventions due to its low cost and portability. However, the main limitation is the limited visibility of surgical tools. We present a new sensor technology that can easily be embedded on needles that are used for US-guided interventions. Two different types of materials are proposed to be used as sensor--co-polymer and PZT. The co-polymer technology is particularly attractive due to its plasticity, allowing very thin depositions (10-20 μm) on a variety of needle shapes. Both sensors receive acoustic energy and convert it to an electrical signal. The precise location of the needle can then be estimated from this signal, to provide real-time feedback to the clinician. We evaluated the feasibility of this new technology using (i) a 4DOF robot in a water tank; (ii) extensive ex vivo experiments; and (iii) in vivo studies. Quantitative robotic studies indicated that the co-polymer is more robust and stable when compared to PZT. In quantitative experiments, the technology achieved a tracking accuracy of 0.14 ± 0.03mm, significantly superior to competing technologies. The technology also proved success in near-real clinical studies on tissue data. This sensor technology is non-disruptive of existing clinical workflows, highly accurate, and is cost-effective. Initial clinician feedback shows great potential for large scale clinical impact.
- Real-time 3D curved needle segmentation using combined B-mode and power Doppler ultrasound. [Journal Article]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):381-8.
This paper presents a real-time segmentation method for curved needles in biological tissue based on analysis of B-mode and power Doppler images from a tracked 2D ultrasound transducer. Mechanical vibration induced by an external voice coil results in a Doppler response along the needle shaft, which is centered around the needle section in the ultrasound image. First, B-mode image analysis is performed within regions of interest indicated by the Doppler response to create a segmentation of the needle section in the ultrasound image. Next, each needle section is decomposed into a sequence of points and transformed into a global coordinate system using the tracked transducer pose. Finally, the 3D shape is reconstructed from these points. The results of this method differ from manual segmentation by 0.71 ± 0.55 mm in needle tip location and 0.38 ± 0.27 mm along the needle shaft. This method is also fast, taking 5-10 ms to run on a standard PC, and is particularly advantageous in robotic needle steering, which involves thin, curved needles with poor echogenicity.
- A quadratic energy minimization framework for signal loss estimation from arbitrarily sampled ultrasound data. [Journal Article, Research Support, Non-U.S. Gov't]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):373-80.
We present a flexible and general framework to iteratively solve quadratic energy problems on a non uniform grid, targeted at ultrasound imaging. Therefore, we model input samples as the nodes of an irregular directed graph, and define energies according to the application by setting weights to the edges. To solve the energy, we derive an effective optimization scheme, which avoids both the explicit computation of a linear system, as well as the compounding of the input data on a regular grid. The framework is validated in the context of 3D ultrasound signal loss estimation with the goal of providing an uncertainty estimate for each 3D data sample. Qualitative and quantitative results for 5 subjects and two target regions, namely US of the bone and the carotid artery, show the benefits of our approach, yielding continuous loss estimates.
- Probe localization for freehand 3D ultrasound by tracking skin features. [Journal Article, Research Support, Non-U.S. Gov't]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):365-72.
Ultrasound probe localization with respect to the patient's body is essential for freehand three-dimensional ultrasound and image-guided intervention. However, current methods for probe localization generally involve bulky and expensive equipment. In this paper, a highly cost-effective and miniature-mobile system is described for 6-DoF probe localization that is robust to rigid patient motion. In this system, skin features in the scan region are recorded at each ultrasound scan acquisition by a lightweight camera rigidly mounted to the probe. A skin map is built based on the skin features and optimal probe poses are estimated in a Bayesian probabilistic framework that incorporates a prior motion model, camera frames, and ultrasound scans. Through freehand scanning on three different body parts, it is shown that on average, for every probe travel distance of 10 mm, the translational and rotational errors are 0.91 ± 0.49 mm and 0.55 degrees ± 0.17 degrees, respectively. The 3D reconstructions were also validated by comparison with real ultrasound scans.
- Predicting fetal neurodevelopmental age from ultrasound images. [Journal Article]
- Med Image Comput Comput Assist Interv 2014; 17(Pt 2):260-7.
We propose an automated framework for predicting age and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. A topology-preserving manifold representation of the fetal skull enabled design of bespoke scale-invariant image features. Our regression forest model used these features to learn a mapping from age-related sonographic image patterns to fetal age and development. The Sylvian Fissure was identified as a critical region for accurate age estimation, and restricting the search space to this anatomy improved prediction accuracy on a set of 130 healthy fetuses (error ± 3.8 days; r = 0.98 performing the best current clinical method. Our framework remained robust when applied to a routine clinical population.