Tracking deforming objects involves estimating the global motion of the object and its local deformations as functions of time. Tracking algorithms using Kalman filters or particle filters (PFs) have been proposed for tracking such objects, but these have limitations due to the lack of dynamic shape information. In this paper, we propose a novel method based on employing a locally linear embedding in order to incorporate dynamic shape information into the particle filtering framework for tracking highly deformable objects in the presence of noise and clutter. The PF also models image statistics such as mean and variance of the given data which can be useful in obtaining proper separation of object and background.
This paper addresses the problem of image segmentation by means of active contours, whose evolution is driven by the gradient flow derived from an energy functional that is based on the Bhattacharyya distance. In particular, given the values of a photometric variable (or of a set thereof), which is to be used for classifying the image pixels, the active contours are designed to converge to the shape that results in maximal discrepancy between the empirical distributions of the photometric variable inside and outside of the contours. The above discrepancy is measured by means of the Bhattacharyya distance that proves to be an extremely useful tool for solving the problem at hand. The proposed methodology can be viewed as a generalization of the segmentation methods, in which active contours maximize the difference between a finite number of empirical moments of the "inside" and "outside" distributions. Furthermore, it is shown that the proposed methodology is very versatile and flexible in the sense that it allows one to easily accommodate a diversity of the image features based on which the segmentation should be performed. As an additional contribution, a method for automatically adjusting the smoothness properties of the empirical distributions is proposed. Such a procedure is crucial in situations when the number of data samples (supporting a certain segmentation class) varies considerably in the course of the evolution of the active contour. In this case, the smoothness properties of the empirical distributions have to be properly adjusted to avoid either over- or underestimation artifacts. Finally, a number of relevant segmentation results are demonstrated and some further research directions are discussed.
In algorithms for processing diffusion tensor images, two common ingredients are interpolating tensors, and measuring the distance between them. We propose a new class of interpolation paths for tensors, termed geodesic-loxodromes, which explicitly preserve clinically important tensor attributes, such as mean diffusivity or fractional anisotropy, while using basic differential geometry to interpolate tensor orientation. This contrasts with previous Riemannian and Log-Euclidean methods that preserve the determinant. Path integrals of tangents of geodesic-loxodromes generate novel measures of over-all difference between two tensors, and of difference in shape and in orientation.
Laparoscopic techniques have gained wide acceptance because they offer a safe and less invasive alternative to open surgery. To further reduce the invasiveness of peritoneal access, the next logical step is to eliminate the incision through the abdominal wall using natural orifices as entry points. This Natural Orifice Transluminal Endoscopic Surgery (NOTES) approach has the potential to replace or augment current techniques. Several research groups have cut through the stomach or colon wall (per-oral transgastric or per-anal transcolonic) to perform organ resections in animal models, and some procedures in humans have been reported anecdotally. Widespread use of these techniques will depend on providing the physician with adequate visual feedback, clear indicators of instrument location and orientation, and support in the recognition of anatomic structures. Compared with laparoscopy, successful endoscopy must accommodate several additional complexities: (1) The flexibility of the endoscope tip complicates the understanding of its distal orientation. Successful navigation inside the stomach and in the abdominal cavity generally requires two years of sub-specialty training. (2) Several surgical targets lie in a retrograde position with respect to an incision in the stomach wall. Efficient and safe access to the pancreas, gall bladder, or the kidneys requires detailed knowledge of the tip placement relative to adjacent anatomic structures. (3) Since there is limited direct access to the abdomen, iatrogenic injuries, such as the accidental cutting of an artery, will be more dangerous and difficult to manage. We present here approaches to resolving these limitations though augmented reality techniques using pre-procedure CT or MRI imaging, real time tracking and reference image registration, and display to the operating physician. As an example, the utility of image registration techniques for orientation for the gastric access puncture is discussed in detail. It is anticipated that such augmentation will make intra-cavitary interventional techniques easier to master and use in practice, and thus more likely to be widely adopted.
OBJECTIVE: Scarless surgery is an innovative and promising technique that may herald a new era in surgical procedures. We have created a navigation system, named IRGUS, for endoscopic and transgastric access interventions and have validated it in in vivo pilot studies. Our hypothesis is that endoscopic ultrasound procedures will be performed more easily and efficiently if the operator is provided with approximately registered 3D and 2D processed CT images in real time that correspond to the probe position and ultrasound image. MATERIALS AND METHODS: The system provides augmented visual feedback and additional contextual information to assist the operator. It establishes correspondence between the real-time endoscopic ultrasound image and a preoperative CT volume registered using electromagnetic tracking of the endoscopic ultrasound probe position. Based on this positional information, the CT volume is reformatted in approximately the same coordinate frame as the ultrasound image and displayed to the operator. RESULTS: The system reduces the mental burden of probe navigation and enhances the operator’s ability to interpret the ultrasound image. Using an initial rigid body registration, we measured the mis-registration error between the ultrasound image and the reformatted CT plane to be less than 5 mm, which is sufficient to enable the performance of novice users of endoscopic systems to approach that of expert users. CONCLUSIONS: Our analysis shows that real-time display of data using rigid registration is sufficiently accurate to assist surgeons in performing endoscopic abdominal procedures. By using preoperative data to provide context and support for image interpretation and real-time imaging for targeting, it appears probable that both preoperative and intraoperative data may be used to improve operator performance.
RATIONALE AND OBJECTIVES: To analyze radiologist lung nodule segmentations in the Lung Imaging Database Consortium (LIDC) database and to apply statistical tools to generate estimates of ground truth. This investigation expands on earlier work by considering a larger number of cases from the LIDC database, and results were generated on a per-nodule basis, as opposed to a per-case basis as was done previously. MATERIALS AND METHODS: We analyzed nodule data drawn from the 41 most recent computed tomography exams released by the LIDC. We combined radiologist segmentations for a given nodule using different consensus schemes: union, intersection, and simultaneous truth and performance level estimation (STAPLE). We also generated three-dimensional models of the manual segmentations using discrete marching cubes to visualize features of the data. RESULTS: Using the union as the consensus scheme produced the greatest number of nodule-positive voxels while using the intersection produced the fewest. Considering only nodules for which all readers agreed on nodule presence, STAPLE computed sensitivity averages for readers one, two, three, and four were 0.91, 0.83, 0.90, and 0.77, respectively. Specificity averages were 0.97, 0.98, 0.97, and 0.97. Considering cases for which there was disagreement about nodule presence, sensitivity results become 0.67, 0.74, 0.60, and 0.37. Specificity results in this case are 0.95, 0.95, 0.95, and 0.98. STAPLE-generated pmaps exhibited probability values tightly grouped below the 0.25 and above the 0.75 probability levels. Three-dimensional models of manually segmented nodules revealed step-artefacts in the segmentation data. CONCLUSIONS: Radiologists often disagree about nodule presence. Ideally, knowing each reader’s sensitivity and specificity a priori is preferred for optimal STAPLE results. Knowing these values and developing manual segmentation tools and imaging protocols that mitigate unwanted segmentation features (such as step artefacts) can result in more accurate estimates of ground truth. Furthermore, a computer-aided detection algorithm’s performance is a function of the ground truth estimate by which it is scored.
BACKGROUND: Appropriateness for lung volume reduction surgery is often determined based on the results of high-resolution CT (HRCT) scanning of the chest. At many centers, radiologists and pulmonary physicians both review the images, but the agreement between readers from these specialties is not known. METHODS: Two thoracic radiologists and three pulmonologists retrospectively reviewed the HRCT scans of 30 patients with emphysema involved in two clinical studies at our institution. Each reader assigned an emphysema severity score and assessed upper lobe predominance, using a methodology similar to that of the National Emphysema Treatment Trial. In addition, the percentage of emphysema at -910 Hounsfield units was objectively determined by density mask analysis.
BACKGROUND: EUS is complicated because of the subtleties of US interpretation, small fields of observation, and uncertainty of probe position and orientation. OBJECTIVE: Improved EUS performance is sought by providing contextual information to support US probe positioning and identification of features in US images. Our aims were to demonstrate the feasibility of the image registered gastroscopic US (IRGUS) system in a porcine model and to compare the effectiveness and the efficiency of IRGUS with traditional EUS. DESIGN: Animal feasibility study. INTERVENTIONS: The IRGUS system uses preprocedure CT and miniature US probe trackers to create real-time synthetic displays of the position of the probe tip and a matched slice of CT data for comparison with the US image. Participants used EUS and IRGUS systems in a porcine model to evaluate the speed and accuracy of structure identification. MAIN OUTCOME MEASUREMENTS: The performance and utility of IRGUS were determined by the number of correctly identified structures in a timed trial, kinematic variables, and a structured survey. RESULTS: IRGUS was twice as effective as EUS in localizing and identifying individual structures. In timed trials, IRGUS users identified over 25% more structures than EUS users. Improvement in examination efficiency and accuracy of feature identification was statistically significant, and 90% of the users preferred IRGUS to EUS for these tasks. CONCLUSIONS: IRGUS appears feasible and may be superior to conventional EUS in efficiency and accuracy of probe positioning and in image interpretation. IRGUS has the potential to shorten the EUS learning curve and to broaden the adoption of EUS techniques by gastroenterologists.
BACKGROUND: The hallmark of COPD is airflow obstruction, but this can develop on the basis of airway disease, emphysema, or both. There are gender differences in the natural history of COPD, and these may in part be explained by differences in the pathophysiology of airflow obstruction. We aimed to determine if there are gender differences in the severity of CT emphysema among COPD patients. METHODS: Current and former smokers enrolled in the National Lung Screening Trial (NLST) at the University of Alabama at Birmingham were recruited at the time of an annual screening CT examination. We recorded demographics and smoking history, and subjects performed spirometry. Subjects were classified into modified (prebronchodilator) Global Initiative for Chronic Obstructive Lung Disease stages, and their CT scans were analyzed to determine regional and total emphysema (defined as the percentage of low attenuation areas [LAA%]; - 950 Hounsfield units). Differences between genders were examined, and univariate and multivariate predictors of LAA% were determined.
Ultrasound imaging systems provide the clinician with noninvasive, low-cost, and real-time images that can help them in diagnosis, planning, and therapy. However, although the human eye is able to derive the meaningful information from these images, automatic processing is very difficult due to noise and artifacts present in the image. The speckle reducing anisotropic diffusion filter was recently proposed to adapt the anisotropic diffusion filter to the characteristics of the speckle noise present in the ultrasound images and to facilitate automatic processing of images. We analyze the properties of the numerical scheme associated with this filter, using a semi-explicit scheme. We then extend the filter to a matrix anisotropic diffusion, allowing different levels of filtering across the image contours and in the principal curvature directions. We also show a relation between the local directional variance of the image intensity and the local geometry of the image, which can justify the choice of the gradient and the principal curvature directions as a basis for the diffusion matrix. Finally, different filtering techniques are compared on a 2-D synthetic image with two different levels of multiplicative noise and on a 3-D synthetic image of a Y-junction, and the new filter is applied on a 3-D real ultrasound image of the liver.
