Biomedical subjects

Wiro J Niessen

Publications and source records attributed to Wiro J Niessen.

15 recordsLinked to original sources

PubMed2004

Noninvasive magnetic resonance to three-dimensional rotational x-ray registration of vertebral bodies for image-guided spine surgery.

STUDY DESIGN: Magnetic resonance (MR) and three-dimensional rotational x-ray (3DRX) images of cadaveric spinal segments were registered using a conventional point-based technique and a noninvasive technique called maximization of mutual information (MMI). OBJECTIVES: To assess the feasibility and accuracy of MMI-based registration in comparison with point-based registration as a new noninvasive image-to-patient registration technique for use in minimally invasive image-guided spine surgery. SUMMARY OF BACKGROUND DATA: In image-guided orthopedic surgery, correspondence between before surgery acquired images and the patient is required. Currently, this necessitates an invasive registration step, in which anatomic landmarks on the bone surface have to be physically touched by a pointer. To overcome this invasive procedure, we propose using a calibrated 3DRX system, a modality that can visualize high contrast objects intraoperatively and that provides a direct correspondence between the image data and the patient. A noninvasive voxel-based technique is used to register the intraoperative 3DRX image to a before surgery acquired MR image. METHODS: Cadaveric thoracic and lumbar spine segments were implanted with markers, which were used as landmarks. The accuracy of the landmark-based registration was compared with MMI-based registration using the residual errors on the marker positions. RESULTS: The errors made using the point-based registration technique were compared with the errors made with MMI. The results show a statistically significant lower error (P < 0.01) for the proposed MMI method. CONCLUSIONS: Noninvasive MMI registration of intraoperative 3DRX images to preoperative MR images is more accurate than point-based registration in cadaveric spine segments. It is therefore a promising technique for replacing the invasive landmark-based registration that is currently used in image-guided spine surgery.

Humans↗

PubMed2004

Semiautomatic segmentation and stenosis quantification of 3D contrast-enhanced MR angiograms of the internal carotid artery.

A technique is presented for the segmentation and quantification of stenosed internal carotid arteries (ICAs) in 3D contrast-enhanced MR angiography (CE-MRA). Segmentation with sub-pixel accuracy of the ICA is achieved via level-set techniques in which the central axis serves as the initialization. The central axis is determined between two user-defined points, and minimal user interaction is required. For quantification, the cross-sectional area is measured in the stenosis and at a reference segment in planes perpendicular to the central axis. The technique was applied to 20 ICAs. The variation in measurements obtained by this method in comparison with manual observations was 8.7%, which is smaller than the interobserver variability among three experts (11.0%).

Algorithms↗

PubMed2004

Interactive segmentation of abdominal aortic aneurysms in CTA images.

A model-based approach to interactive segmentation of abdominal aortic aneurysms from CTA data is presented. After manual delineation of the aneurysm sac in the first slice, the method automatically detects the contour in subsequent slices, using the result from the previous slice as a reference. If an obtained contour is not sufficiently accurate, the user can intervene and provide an additional manual reference contour. The method is inspired by the active shape model (ASM) segmentation scheme (), in which a statistical shape model, derived from corresponding landmark points in manually labeled training images, is fitted to the image in an iterative manner. In our method, a shape model of the contours in two adjacent image slices is progressively fitted to the entire volume. The contour obtained in one slice thus constrains the possible shapes in the next slice. The optimal fit is determined on the basis of multi-resolution gray level models constructed from gray value patches sampled around each landmark. We propose to use the similarity of adjacent image slices for this gray level model, and compare these to single-slice features that are more generally used with ASM. The performance of various image features is evaluated in leave-one-out experiments on 23 data sets. Features that use the similarity of adjacent image slices outperform measures based on single-slice features in all cases. The average number of slices in our datasets is 51, while on average eight manual initializations are required, which decreases operator segmentation time by a factor of 6.

Algorithms↗

PubMed2004

Analysis of cerebral infarction pattern in computed tomography images of patients with internal carotid artery stenosis.

RATIONALE AND OBJECTIVES: An unbiased and quantitative analysis of lesion patterns in patient groups is described and applied to the analysis of infarction patterns. MATERIALS AND METHODS: One hundred forty-two computed tomographic images of patients with ischemic stroke were registered to an average computed tomographic brain image, which was used as template. Lesions were segmented manually and averaged per category of internal carotid artery (ICA) stenosis. Thus, patterns of lesion distribution were formed. Differences then were analyzed using nonparametric statistics. This analysis was compared with the traditional classification of lesions. RESULTS: The nonparametric analysis showed an increased involvement of the territory of the middle cerebral artery in infarctions in patients with ICA occlusion compared with patients with mild or severe ICA stenosis. These differences did not show when classification of infarctions was used. CONCLUSIONS: The presented method is more sensitive to differences in lesion patterns than traditional lesion classification and showed a different infarction pattern for ICA occlusion.

Aged↗

PubMed2004

Evaluation of semiautomated internal carotid artery stenosis quantification from 3-dimensional contrast-enhanced magnetic resonance angiograms.

RATIONALE AND OBJECTIVES: The performance of a semiautomatic technique for internal carotid artery (ICA) stenosis quantification of the internal carotid artery in contrast-enhanced magnetic resonance angiography was evaluated. MATERIALS AND METHODS: The degree of stenosis of 52 ICAs was quantified by measuring the cross-sectional area along the center lumen line. This was performed both by 3 independent observers and the semiautomated method. The degree of stenosis was defined as the amount of cross-sectional lumen reduction. RESULTS: Agreement between the method and observers was good (weighted-kappa, kappaW = 0.89). Reproducibility of measurements of the semiautomated technique was better (kappaW = 0.97) than that of the observers (kappaW = 0.76), and the evaluated technique was considerably less time-consuming. CONCLUSIONS: Because the user interaction is limited, this technique can be used to replace an expert observer in 3-dimensional stenosis quantification of the ICA at CE-MRA in clinical practice.

Aged↗

PubMed2004

Multiscale vessel tracking.

A method is presented that uses a vectorial multiscale feature image for wave front propagation between two or more user defined points to retrieve the central axis of tubular objects in digital images. Its implicit scale selection mechanism makes the method more robust to overlap and to the presence of adjacent structures than conventional techniques that propagate a wave front over a scalar image representing the maximum of a range of filters. The method is shown to retain its potential to cope with severe stenoses or imaging artifacts and objects with varying widths in simulated and actual two-dimensional angiographic images.

Algorithms↗

PubMed2003

Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.

Algorithms↗

PubMed2003

Endpoint localization in guide wire tracking during endovascular interventions.

RATIONALE AND OBJECTIVES: A method is presented to track guide wires during endovascular interventions under X-ray fluoroscopy. Accurate guide wire tracking can be used to improve guide wire visualization in the low quality fluoroscopic images, and to estimate the position of the guide wire in world coordinates for navigation purposes. MATERIALS AND METHODS: A two-step procedure is used to track the guide wire in subsequent frames. First, the position of the guide wire is obtained by fitting a spline to the image. Subsequently, the spline is iteratively moved toward the tip of the guide wire for accurate tip localization. For both steps, a feature image is used in which line-like structures are enhanced. The method is validated using a reference standard, obtained by manual tracings of three observers. RESULTS: The method is evaluated on 20 image sequences, 10 sequences with a J-tipped guide wire and 10 with a straight guide wire. The tracking success was 96% for J-tipped and 100% for straight guide wires, whereas accurate endpoint localization could be performed in 91.3% and 94.4% of the frames respectively, with a tip localization error of less than 1.5 mm. CONCLUSIONS: Accurate endpoint localization can be performed for both J-tipped and straight guide wires and therefore the presented tracking method can be used for navigation purposes.

Algorithms↗

PubMed2003

Localization and segmentation of aortic endografts using marker detection.

A method for localization and segmentation of bifurcated aortic endografts in computed tomographic angiography (CTA) images is presented. The graft position is determined by detecting radiopaque markers sewn on the outside of the graft. The user indicates the first and the last marker, whereupon the remaining markers are automatically detected. This is achieved by first detecting marker-like structures through second-order scaled derivative analysis, which is combined with prior knowledge of graft shape and marker configuration. The identified marker centers approximate the graft sides and, derived from these, the central axis. The graft boundary is determined by maximizing the local gradient in the radial direction along a deformable contour passing through both sides. Three segmentation methods were tested. The first performs graft contour detection in the initial CT-slices, the second in slices that were reformatted to be orthogonal to the approximated graft axis, and the third uses the segmentation from the second method to find a more reliable approximation of the axis and subsequently performs contour detection. The methods have been applied to ten CTA images and the results were compared to manual marker indication by one observer and region growing aided segmentation by three observers. Out of a total of 266 markers, 262 were detected. Adequate approximations of the graft sides were obtained in all cases. The best segmentation results were obtained using a second iteration orthogonal to the axis determined from the first segmentation, yielding an average relative volume of overlap with the expert segmentations of 92%, while the interexpert reproducibility is 95%. The averaged difference in volume measured by the automated method and by the experts equals the difference among the experts: 3.5%.

Anatomy, Cross-Sectional↗

PubMed2003

Blood pool contrast-enhanced MRA: improved arterial visualization in the steady state.

Blood pool agents (BPAs) for contrast-enhanced magnetic resonance angiography (CE-MRA) allow prolonged imaging during the steady state when the agent is distributed through the complete vascular system. This increases both the spatial resolution and the contrast resolution. However, simultaneous venous and arterial enhancement hampers interpretation. For the pelvic region of the vasculature, it is shown that arterial visualization in this equilibrium phase can be improved if the central arterial axis (CAA) is known. However, manually obtaining this axis is not feasible in clinical practice. Therefore, a method is presented that utilizes images acquired during the first pass of the contrast agent to find the CAA in the steady-state data with minimum user initialization. The accuracy of the resulting CAA is compared with tracings of three observers in six patient datasets. It was found that the mean difference between the semiautomatic method and the manual delineation is 1.32 mm in the steady-state data, and that the resulting CAA was always within the arterial lumen, which is an important prerequisite for both improved visualization and segmentation.

Algorithms↗

PubMed2003

Guide-wire tracking during endovascular interventions.

A method is presented to extract and track the position of a guide wire during endovascular interventions under X-ray fluoroscopy. The method can be used to improve guide-wire visualization in low-quality fluoroscopic images and to estimate the position of the guide wire in world coordinates. A two-step procedure is utilized to track the guide wire in subsequent frames. First, a rough estimate of the displacement is obtained using a template-matching procedure. Subsequently, the position of the guide wire is determined by fitting a spline to a feature image. The feature images that have been considered enhance line-like structures on: 1) the original images; 2) subtraction images; and 3) preprocessed images in which coherent structures are enhanced. In the optimization step, the influence of the scale at which the feature is calculated and the additional value of using directional information is investigated. The method is evaluated on 267 frames from ten clinical image sequences. Using the automatic method, the guide wire could be tracked in 96% of the frames, with a similar accuracy to three observers, although the position of the tip was estimated less accurately.

Algorithms↗

PubMed2003

Level-set-based artery-vein separation in blood pool agent CE-MR angiograms.

Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved.

Algorithms↗

PubMed2003

Three-dimensional guide-wire reconstruction from biplane image sequences for integrated display in 3-D vasculature.

Using three-dimensional rotational X-ray angiography (3DRA), three-dimensional (3-D) information of the vasculature can be obtained prior to endovascular interventions. However, during interventions, the radiologist has to rely on fluoroscopy images to manipulate the guide wire. In order to take full advantage of the 3-D information from 3DRA data during endovascular interventions, a method is presented that yields an integrated display of the position of the guide wire and vasculature in 3-D. The method relies on an automated method that tracks the guide wire simultaneously in biplane fluoroscopy images. Based on the calibrated geometry of the C-arm, the 3-D guide-wire position is determined and visualized in the 3-D coordinate system of the vasculature. The method is evaluated in an intracranial anthropomorphic vascular phantom. The influence of the angle between projections, distortion correction of the projection images, and accuracy of geometry knowledge on the accuracy of 3-D guide-wire reconstruction from biplane images is determined. If the calibrated geometry information is used and the images are corrected for distortion, a mean distance to the reference standard of 0.42 mm and a tip distance of 0.65 mm is found, which means that accurate guide-wire reconstruction from biplane images can be performed.

Algorithms↗

PubMed2002

3D MRA coronary axis determination using a minimum cost path approach.

A method is introduced to automatically find the coronary axis based on two or more user-defined points, even in the presence of a severe stenosis. The coronary axis is determined by finding a minimum cost path (MCP) in a feature image in which the tubular-like structures are enhanced. The results of the proposed method were compared with manually drawn central axes to estimate the accuracy. In 32 3D TFE-EPI acquisitions of patients and volunteers, 14 right coronary arteries (RCAs), 15 left anterior descending arteries (LADs), and eight left circumflex arteries (LCXs) were manually tracked twice by two operators to determine a reference axis and to assess the inter- and intra-user variability. On average, the maximum distance to the reference axis, based on only two user-defined points, is less than 1.5 mm; the average distance is around 0.65 mm, which is less than the average in-plane resolution. The results of the method are comparable to those of the manual operators.

Coronary Stenosis↗

PubMed2002

Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling.

A novel method is introduced for the generation of landmarks for three-dimensional (3-D) shapes and the construction of the corresponding 3-D statistical shape models. Automatic landmarking of a set of manual segmentations from a class of shapes is achieved by 1) construction of an atlas of the class, 2) automatic extraction of the landmarks from the atlas, and 3) subsequent propagation of these landmarks to each example shape via a volumetric nonrigid registration technique using multiresolution B-spline deformations. This approach presents some advantages over previously published methods: it can treat multiple-part structures and requires less restrictive assumptions on the structure's topology. In this paper, we address the problem of building a 3-D statistical shape model of the left and right ventricle of the heart from 3-D magnetic resonance images. The average accuracy in landmark propagation is shown to be below 2.2 mm. This application demonstrates the robustness and accuracy of the method in the presence of large shape variability and multiple objects.

Algorithms↗