3D stereo interactive medical visualization.
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Imaging, Three-Dimensional↗
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Results for “Photogrammetry”
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Magic lenses for augmented virtual environments.
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Algorithms↗
Microcomputer generation of dynamic stereo graphics for clinical use.
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Computers↗
Three-dimensional localization of cochlear implant electrodes using epipolar stereophotogrammetry.
Three-dimensional (3-D) localization of individual cochlear implant electrodes within the inner ear is of importance for modeling the electrical field of the cochlea, designing the electrode array, and programming the associated speech processor. A 3-D reconstruction method of cochlear implant electrodes is proposed to localize individual electrodes from two X-ray views in combination with the spiral computed tomography technique. By adapting epipolar geometry to the configuration of an X-ray imaging system, we estimate individual electrode locations in the least square sense without using a patient attachment required by an existing stereophotogrammetry technique. Furthermore, our method does not require any knowledge of the intrinsic and extrinsic parameters of the imaging system. The performance of our method is studied in numerical simulation and with patient data and is found to be sufficiently accurate for clinical use. The maximum root mean-square errors measured are 0.0445 and 0.214 mm for numerical simulation and patient data, respectively.
Cochlea↗
3-D reconstruction of microcalcification clusters using stereo imaging: algorithm and mammographic unit calibration.
The three-dimensional (3-D) shape of microcalcification clusters is an important indicator in early breast cancer detection. In fact, there is a relationship between the cluster topology and the type of lesion (malignant or benign). This paper presents a 3-D reconstruction method for such clusters using two 2-D views acquired during standard mammographic examinations. For this purpose, the mammographic unit was modeled using a camera with virtual optics. This model was used to calibrate the acquisition unit and then to reconstruct the clusters in the 3-D space after microcalcification segmentation and matching. The proposed model is hardware independent since it is suitable for digital mammographic units with different geometries and with various physical acquisition principles. Three-dimensional reconstruction results are presented here to prove the validity of the method. Tests were first performed using a phantom with a well-known geometry. The latter contained X-ray opaque glass balls representing microcalcifications. The positions of these balls were reconstructed with a 16.25-microm mean accuracy. This very high inherent algorithm accuracy is more than enough for a precise 3-D cluster representation. Further validation tests were carried out using a second phantom including a spherical cluster. This phantom was built with materials simulating the behavior of both mammary tissue and microcalcifications toward Xrays. The reconstructed shape was effectively spherical. Finally, reconstructions were carried out for real clusters and their results are also presented.
Algorithms↗
Face localization and authentication using color and depth images.
This paper presents a complete face authentication system integrating both two-dimensional (color or intensity) and three-dimensional (3-D) range data, based on a low-cost 3-D sensor, capable of real-time acquisition of 3-D and color images. Novel algorithms are proposed that exploit depth information to achieve robust face detection and localization under conditions of background clutter, occlusion, face pose alteration, and harsh illumination. The well-known embedded hidden Markov model technique for face authentication is applied to depth maps and color images. To cope with pose and illumination variations, the enrichment of face databases with synthetically generated views is proposed. The performance of the proposed authentication scheme is tested thoroughly on two distinct face databases of significant size. Experimental results demonstrate significant gains resulting from the combined use of depth and color or intensity information.
Algorithms↗
Image registration using log-polar mappings for recovery of large-scale similarity and projective transformations.
This paper describes a novel technique to recover large similarity transformations (rotation/scale/translation) and moderate perspective deformations among image pairs. We introduce a hybrid algorithm that features log-polar mappings and nonlinear least squares optimization. The use of log-polar techniques in the spatial domain is introduced as a preprocessing module to recover large scale changes (e.g., at least four-fold) and arbitrary rotations. Although log-polar techniques are used in the Fourier-Mellin transform to accommodate rotation and scale in the frequency domain, its use in registering images subjected to very large scale changes has not yet been exploited in the spatial domain. In this paper, we demonstrate the superior performance of the log-polar transform in featureless image registration in the spatial domain. We achieve subpixel accuracy through the use of nonlinear least squares optimization. The registration process yields the eight parameters of the perspective transformation that best aligns the two input images. Extensive testing was performed on uncalibrated real images and an array of 10,000 image pairs with known transformations derived from the Corel Stock Photo Library of royalty-free photographic images.
Algorithms↗
Is image steganography natural?
Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. We experimentally investigate if stego-images, bearing a secret message, are statistically "natural." For this purpose, we use recent results on the statistics of natural images and investigate the effect of some popular steganography techniques. We found that these fundamental statistics of natural images are, in fact, generally altered by the hidden "nonnatural" information. Frequently, the change is consistently biased in a given direction. However, for the class of natural images considered, the change generally falls within the intrinsic variability of the statistics, and, thus, does not allow for reliable detection, unless knowledge of the data hiding process is taken into account. In the latter case, significant levels of detection are demonstrated.
Algorithms↗
3-D shape estimation of DNA molecules from stereo cryo-electron micro-graphs using a projection-steerable snake.
We introduce a three-dimensional (3-D) parametric active contour algorithm for the shape estimation of DNA molecules from stereo cryo-electron micrographs. We estimate the shape by matching the projections of a 3-D global shape model with the micrographs; we choose the global model as a 3-D filament with a B-spline skeleton and a specified radial profile. The active contour algorithm iteratively updates the B-spline coefficients, which requires us to evaluate the projections and match them with the micrographs at every iteration. Since the evaluation of the projections of the global model is computationally expensive, we propose a fast algorithm based on locally approximating it by elongated blob-like templates. We introduce the concept of projection-steerability and derive a projection-steerable elongated template. Since the two-dimensional projections of such a blob at any 3-D orientation can be expressed as a linear combination of a few basis functions, matching the projections of such a 3-D template involves evaluating a weighted sum of inner products between the basis functions and the micrographs. The weights are simple functions of the 3-D orientation and the inner-products are evaluated efficiently by separable filtering. We choose an internal energy term that penalizes the average curvature magnitude. Since the exact length of the DNA molecule is known a priori, we introduce a constraint energy term that forces the curve to have this specified length. The sum of these energies along with the image energy derived from the matching process is minimized using the conjugate gradients algorithm. We validate the algorithm using real, as well as simulated, data and show that it performs well.
Algorithms↗
Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.
This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.
Algorithms↗
A mesh-based disparity representation method for view interpolation and stereo image compression.
This paper proposes a mesh-based representation method for the disparity map of stereo images. The proposed method is designed to concentrate mainly on applications of view interpolation and stereo image compression. To obtain high image quality in the view interpolation and compression of stereo images, we formulate the view-interpolation error and prediction error. In the formulation, the view-interpolation and prediction errors depend not only on the accuracy of the disparity map, but also on the gradient of the stereo images. The proposed representation method for the disparity map is based on a triangular mesh structure, which minimizes the formulated interpolation and prediction errors. The experimental results show that the proposed method yields higher quality view-interpolated images and also has better performance in stereo image compression than the conventional methods.
Algorithms↗
Camera calibration using symmetric objects.
This paper proposes a novel method for camera calibration using images of a mirror symmetric object. Assuming unit aspect ratio and zero skew, we show that interimage homographies can be expressed as a function of only the principal point. By minimizing symmetric transfer errors, we thus obtain an accurate solution for the camera parameters. We also extend our approach to a calibration technique using images of a 1-D object with a fixed pivoting point. Unlike existing methods that rely on orthogonality or pole-polar relationship, our approach utilizes new inter-image constraints and does not require knowledge of the 3-D coordinates of feature points. To demonstrate the effectiveness of the approach, we present results for both synthetic and real images.
Algorithms↗
Digital stereo image analyzer for generating automated 3-D measures of optic disc deformation in glaucoma.
The major limitations of precise evaluation of retinal structures in present clinical situations are the lack of standardization, the inherent subjectivity involved in the interpretation of retinal images, and intra- as well as interobserver variability. While evaluating optic disc deformation in glaucoma, these limitations could be overcome by using advanced digital image analysis techniques to generate precise metrics from stereo optic disc image pairs. A digital stereovision system for visualizing the topography of the optic nerve head from stereo optic disc images is presented. We have developed an algorithm, combining power cepstrum and zero-mean-normalized cross correlation techniques, which extracts depth information using coarse-to-fine disparity between corresponding windows in a stereo pair. The gray level encoded sparse disparity matrix is subjected to a cubic B-spline operation to generate smooth representations of the optic cup/disc surfaces and new three-dimensional (3-D) metrics from isodisparity contours. Despite the challenges involved in 3-D surface recovery, the robustness of our algorithm in finding disparities within the constraints used has been validated using stereo pairs with known disparities. In a preliminary longitudinal study of glaucoma patients, a strong correlation is found between the computer-generated quantitative cup/disc volume metrics and manual metrics commonly used in a clinic. The computer generated new metrics, however, eliminate the subjective variability and greatly reduce the time and cost involved in manual metric generation in follow-up studies of glaucoma.
Algorithms↗
Heart-surface reconstruction and ECG electrodes localization using fluoroscopy, epipolar geometry and stereovision: application to noninvasive imaging of cardiac electrical activity.
To date there is no imaging modality for cardiac arrhythmias which remain the leading cause of sudden death in the United States (> 300000/yr.). Electrocardiographic imaging (ECGI), a noninvasive modality that images cardiac arrhythmias from body surface potentials, requires the geometrical relationship between the heart surface and the positions of body surface ECG electrodes. A photographic method was validated in a mannequin and used to determine the three-dimensional coordinates of body surface ECG electrodes to within 1 mm of their actual positions. Since fluoroscopy is available in the cardiac electrophysiology (EP) laboratory where diagnosis and treatment of cardiac arrhythmias is conducted, a fluoroscopic method to determine the heart surface geometry was developed based on projective geometry, epipolar geometry, point reconstruction, b-spline interpolation and visualization. Fluoroscopy-reconstructed hearts in a phantom and a human subject were validated using high-resolution computed tomography (CT) imaging. The mean absolute distance error for the fluoroscopy-reconstructed heart relative to the CT heart was 4 mm (phantom) and 10 mm (human). In the human, ECGI images of normal cardiac electrical activity on the fluoroscopy-reconstructed heart showed close correlation with those obtained on the CT heart. Results demonstrate the feasibility of this approach for clinical noninvasive imaging of cardiac arrhythmias in the interventional EP laboratory.
Algorithms↗
Tooth segmentation of dental study models using range images.
The accurate segmentation of the teeth from the digitized representation of a dental study model is an important component in computer-based algorithms for orthodontic feature detection and measurement and in the simulation of orthodontic procedures such as tooth rearrangement. This paper presents an automated method for tooth segmentation from the three-dimensional (3-D) digitized image captured by a laser scanner. We avoid the complexity of directly processing 3-D mesh data by proposing the innovative idea of detecting features on two range images computed from the 3-D image. The dental arch is first obtained from the plan-view range image. Using the arch as the reference, a panoramic range image of the dental model can be computed. The interstices between the teeth are detected separately in the two range images, and results from both views are combined for a determination of interstice locations and orientations. Finally, the teeth are separated from the gums by delineating the gum margin. The algorithm was tested on 34 dental models representing a variety of malocclusions and was found to be robust and accurate.
Algorithms↗
High-resolution 3-D shape integration of dentition and face measured by new laser scanner.
Face and dentition were measured using a high-resolution three-dimensional laser scanner to circumvent problems of radiation exposure and metal-streak artifacts associated with X-ray computed tomography. The resulting range data were integrated in order to visualize the dentition relative to the face. The acquisition interval for dentition by laser scanner was 0.18 mm, and complicated morphologies of the occlusal surface could be sufficiently reproduced. Reproduction of occlusal condition of upper and lower dentitions was conducted by matching the surface of the occlusal impression record with upper dentition data. To integrate dentition and face, a marker plate interface was devised and adopted on the lower dental cast or by the subject directly. Integration was performed by matching both sets of interface data. Reproduction of the occlusal condition and integration of the dentition and face were accomplished and visualized satisfactorily by computer graphics. The integration accuracy was examined by changing the attachment angle of the marker plate, and the marker plate attached at 45 degrees showed the smallest error of 0.2 mm. The current noninvasive method is applicable to clinical examination, diagnosis and explanation to the patient when dealing with the physical relationship between face and dentition.
Adult↗
Stereopsis-guided brain shift compensation.
Brain deformation models have proven to be a powerful tool in compensating for soft tissue deformation during image-guided neurosurgery. The accuracy of these models can be improved by incorporating intraoperative measurements of brain motion. We have designed and implemented a passive intraoperative stereo vision system capable of estimating the three-dimensional shape of the surgical scene in near real-time. This intraoperative shape is compared with the cortical surface in the co-registered preoperative magnetic resonance (MR) volume for the estimation of the cortical motion resulting from the open cranial surgery. The estimated cortical motion is then used to guide a full brain model, which updates a preoperative MR volume. We have found that the stereo vision system is accurate to within approximately 1 mm. Based on data from two representative clinical cases, we show that stereopsis guidance improves the accuracy of brain shift compensation both at and below the cortical surface.
Algorithms↗
Augmented virtuality based on stereoscopic reconstruction in multimodal image-guided neurosurgery: methods and performance evaluation.
Displaying anatomical and physiological information derived from preoperative medical images in the operating room is critical in image-guided neurosurgery. This paper presents a new approach referred to as augmented virtuality (AV) for displaying intraoperative views of the operative field over three-dimensional (3-D) multimodal preoperative images onto an external screen during surgery. A calibrated stereovision system was set up between the surgical microscope and the binocular tubes. Three-dimensional surface meshes of the operative field were then generated using stereopsis. These reconstructed 3-D surface meshes were directly displayed without any additional geometrical transform over preoperative images of the patient in the physical space. Performance evaluation was achieved using a physical skull phantom. Accuracy of the reconstruction method itself was shown to be within 1 mm (median: 0.76 mm +/- 0.27), whereas accuracy of the overall approach was shown to be within 3 mm (median: 2.29 mm +/- 0.59), including the image-to-physical space registration error. We report the results of six surgical cases where AV was used in conjunction with augmented reality. AV not only enabled vision beyond the cortical surface but also gave an overview of the surgical area. This approach facilitated understanding of the spatial relationship between the operative field and the preoperative multimodal 3-D images of the patient.
Algorithms↗