Ali Khamene

Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention.

The fusion of tracked ultrasound with CT has benefits for a variety of clinical applications, however extensive manual effort is usually required for correct registration. We developed new methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects. They are combined with a robust similarity measure that assesses the correlation of a combination of signals extracted from CT with ultrasound, without knowing the influence of each signal. This serves as the foundation of a fully automatic registration, that aligns a 3D ultrasound sweep with the corresponding tomographic modality using a rigid or an affine transformation model, without any manual interaction. These techniques were evaluated in a study involving 25 patients with indeterminate lesions in liver and kidney. The clinical setup, acquisition and registration workflow is described, along with the evaluation of the registration accuracy with respect to physician-defined Ground Truth. Our new algorithm correctly registers without any manual interaction in 76% of the cases, the average RMS TRE over multiple target lesions throughout the liver is 8.1mm.

A new method for the extraction of fetal ECG from the composite abdominal signal

We developed a wavelet transform-based method to extract the fetal electrocardiogram (ECG) from the composite abdominal signal. This is based on the detection of the singularities obtained from the composite abdominal signal, using the modulus maxima in the wavelet domain. Modulus maxima locations of the abdominal signal are used to discriminate between maternal and fetal ECG signals. Two different approaches have been considered, In the first approach, at least one thoracic signal is used as the a prior to perform the classification whereas in the second approach no thoracic signal is needed, A reconstruction method is utilized to obtain the fetal ECG signal from the detected fetal modulus maxima. The proposed technique is different from the classical time-domain methods, in that we exploit the most distinct features of the signal, leading to more robustness with respect to signal perturbations. Results of experiments with both synthetic and real ECG data have been presented to demonstrate the efficacy of the proposed method.

Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy

The efficacy of radiation therapy treatment depends on the patient setup accuracy at each daily fraction. A significant problem is reproducing the patient position during treatment planning for every fraction of the treatment process. We propose and evaluate an intensity based automatic registration method using multiple portal images and the pre-treatment CT volume. We perform both geometric and radiometric calibrations to generate high quality digitally reconstructed radiographs (DRRs) that can be compared against portal images acquired right before treatment dose delivery. We use a graphics processing unit (GPU) to generate the DRRs in order to gain computational efficiency. We also perform a comparative study on various similarity measures and optimization procedures. Simple similarity measure such as local normalized correlation (LNC) performs best as long as the radiometric calibration is carefully done. Using the proposed method, we achieved better than 1mm average error in repositioning accuracy for a series of phantom studies using two open field (i.e., 41 cm2) portal images with 90 degrees vergence angle.

Simulation and fully automatic multimodal registration of medical ultrasound

The fusion of 3D freehand ultrasound with CT and CTA has benefits for a variety of clinical applications, however a lot of manual work is usually required for correct registration. We developed new methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects. The second novelty is a robust similarity measure that assesses the correlation of a combination of multiple signals extracted from CT with ultrasound, without knowing the influence of each signal. This serves as the foundation of a fully automatic registration, which aligns a freehand ultrasound sweep with the corresponding 3D modality using a rigid or an affine transformation model, without any manual interaction. We also present the used initialization, global and local parameter optimization schemes, and validation on abdominal CTA and ultrasound imaging of 10 patients.

Constrained surface evolutions for prostate and bladder segmentation in CT images

We propose a Bayesian formulation for coupled surface evolutions and apply it to the segmentation of the prostate and the bladder in CT images. This is of great interest to the radiotherapy treatment process, where an accurate contouring of the prostate and its neighboring organs is needed. A purely data based approach fails, because the prostate boundary is only partially visible. To resolve this issue, we define a Bayesian framework to impose a shape constraint on the prostate, while coupling its extraction with that of the bladder. Constraining the segmentation process makes the extraction of both organs’ shapes more stable and more accurate. We present some qualitative and quantitative results on a few data sets, validating the performance of the approach.

A novel phantom-less spatial and temporal ultrasound calibration method

This paper introduces a novel method for ultrasound calibration for both spatial and temporal parameters. The main advantage of this method is that it does not require a phantom, which is usually expensive to fabricate. Furthermore, the method does not require extensive image processing. For spatial calibration, we solve an optimization problem established by a set of equations that relate the orientations of a line (i.e., calibration pointer) to the intersection points appearing in the ultrasound image. The line orientation is provided through calibration of both ends of the calibration pointer. Temporal calibration is achieved by processing of the captured pointer orientations and the corresponding image positions of intersection along with the timing information. The effectiveness of the unified method for both spatial and temporal calibration is apparent from the quality of the 3D reconstructions of a known object.

An Augmented Reality Navigation System with a Single-Camera Tracker: System Design and Needle Biopsy Phantom Trial

We extended a system for augmented reality visualization to include the capability for instrument tracking. The original system is based on a videosee-through head-mounted display and features single-camera tracking. The tracking camera is head-mounted, rigidly fixed to a stereo pair of cameras that provide a live video view of a workspace. The tracker camera includes an infrared illuminator and works in conjunction with a set of retroreflective markers that are placed around the workspace. This marker frame configuration delivers excellent pose information for a stable overlay of graphics onto the video images. Using the single camera also for instrument tracking with relatively small marker clusters, however, encounters problems of marker identification and of noise in the pose data. We present a multilevel planar marker design, which we used to build a needle placement phantom. In this phantom, we achieved a stable augmentation; the user can see the location of the hidden target and the needle without perceptible jitter of the overlaid graphics. Piercing the needle through a foam window and hitting the target is then intuitive and comfortable. Over a hundred users have tested the system, and are consistently able to correctly place the needle on the 6mm target without prior training.

Single camera tracking of marker clusters: multiparameter cluster optimization and experimental verification

We have built a system for augmented reality visualization based on a single head mounted tracking camera. The camera includes an infrared illuminator and works in conjunction with a set of retro-reflective markers that are placed around the workspace. This marker frame configuration delivers excellent pose information, which translates to stable, jitter-free augmentation. In this article, we describe using the same single camera system for tracking relatively small marker clusters, which can be used for tool or instrument tracking. Tracking of such a marker cluster is more susceptible to noise compared to tracking of a marker frame, mainly due to its small image coverage. The sensitivity to noise is studied using Monte Carlo simulations and verified in an experimental setup. We achieved jitter-free augmentation with an optimized cluster design.

Fast deformable registration of 3d-ultrasound data using a variational approach

We present an intensity based deformable registration algorithm for 3D ultrasound data. The proposed method uses a variational approach and combines the characteristics of a multilevel algorithm and the properties of ultrasound data in order to provide a fast and accurate deformable registration method. In contrast to previously proposed approaches, we use no feature points and no interpolation technique, but compute a dense displacement field directly. We demonstrate that this approach, although it includes solving large PDE systems, reduces the computation time if implemented using efficient numerical techniques. The performance of the algorithm is tested on multiple 3D US images of the liver. Validation is performed by simulations, similarity comparisons between original and deformed images, visual inspection of the displacement fields and visual assessment of the deformed images by physicians.

Standardized platform for coregistration of nonconcurrent diffuse optical and magnetic resonance breast images obtained in different geometries

We present a novel methodology for combining breast image data obtained at different times, in different geometries, and by different techniques. We combine data based on diffuse optical tomography (DOT) and magnetic resonance imaging (MRI). The software platform integrates advanced multimodal registration and segmentation algorithms, requires minimal user experience, and employs computationally efficient techniques. The resulting superposed 3-D tomographs facilitate tissue analyses based on structural and functional data derived from both modalities, and readily permit enhancement of DOT data reconstruction using MRI-derived a-priori structural information. We demonstrate the multimodal registration method using a simulated phantom, and we present initial patient studies that confirm that tumorous regions in a patient breast found by both imaging modalities exhibit significantly higher total hemoglobin concentration (THC) than surrounding normal tissues. The average THC in the tumorous regions is one to three standard deviations larger than the overall breast average THC for all patients.