Biomedical subjects

Max A Viergever

Publications and source records attributed to Max A Viergever.

At least 19 recordsLinked to original sources

PubMed2006

Statistical reconstruction for x-ray CT systems with non-continuous detectors.

We analyse the performance of statistical reconstruction (SR) methods when applied to non-continuous x-ray detectors. Robustness to projection gaps is required in x-ray CT systems with multiple detector modules or with defective detector pixels. In such situations, the advantage of statistical reconstruction is that it is able to ignore missing or faulty pixels and that it makes optimal use of the remaining line integrals. This potentially obviates the need to fill the sinogram discontinuities by interpolation or any other approximative pre-processing techniques. In this paper, we apply SR to cone beam projections of (i) a hypothetical modular detector micro-CT scanner and of (ii) a system with randomly located defective detector elements. For the modular-detector system, SR produces reconstruction volumes free of noticeable gap-induced artefacts as long as the location of detector gaps and selection of the scanning range provide complete object sampling in the central imaging plane. When applied to randomly located faulty detector elements, SR produces images free of substantial ring artefacts even for cases where defective pixels cover as much as 3% of the detector area.

Algorithms↗

PubMed2006

Automatic rib segmentation and labeling in computed tomography scans using a general framework for detection, recognition and segmentation of objects in volumetric data.

A system for automatic segmentation and labeling of the complete rib cage in chest CT scans is presented. The method uses a general framework for automatic detection, recognition and segmentation of objects in three-dimensional medical images. The framework consists of five stages: (1) detection of relevant image structures, (2) construction of image primitives, (3) classification of the primitives, (4) grouping and recognition of classified primitives and (5) full segmentation based on the obtained groups. For this application, first 1D ridges are extracted in 3D data. Then, primitives in the form of line elements are constructed from the ridge voxels. Next a classifier is trained to classify the primitives in foreground (ribs) and background. In the grouping stage centerlines are formed from the foreground primitives and rib numbers are assigned to the centerlines. In the final segmentation stage, the centerlines act as initialization for a seeded region growing algorithm. The method is tested on 20 CT-scans. Of the primitives, 97.5% is classified correctly (sensitivity is 96.8%, specificity is 97.8%). After grouping, 98.4% of the ribs are recognized. The final segmentation is qualitatively evaluated and is very accurate for over 80% of all ribs, with slight errors otherwise.

Algorithms↗

PubMed2006

Vessel enhancing diffusion: a scale space representation of vessel structures.

A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom data and compared to linear, regularized Perona-Malik, edge and coherence enhancing diffusion. The method performs better than most of the existing techniques in visualizing vessels with varying radii and in enhancing vessel appearance. A diameter study on phantom data shows that VED least affects the accuracy of diameter measurements. It is shown that using VED as a preprocessing step improves level set based segmentation of the cerebral vasculature, in particular segmentation of the smaller vessels of the vasculature.

Anisotropy↗

PubMed2005

The effect of B1 field inhomogeneity and the nonselective inversion profile on the kinetics of FAIR-based perfusion MRI.

Perfusion imaging with pulsed arterial spin labeling techniques, like flow-sensitive alternating inversion recovery (FAIR), may suffer from inflow of fresh, i.e., unlabeled, spins. Inflow of fresh spins is caused by the arrival of unlabeled spins in the image slice and can lead to underestimation of the perfusion if not taken into account. In this study it was shown that a decrease in B(1) field strength toward the edge of the transmit coil and the consequent reduction in the inversion efficiency leads to a narrowing of the arterial delivery function and a reduction in FAIR signal. Increasing the B(1) amplitude of the adiabatic inversion pulse from 2.3 to 5.7 times its minimum amplitude requirement resulted in an observed increase of 40 to 80% in the rat brain FAIR signal at inflow times longer than 0.65 s. For coils with limited dimensions and significant B(1) inhomogeneity over the perfusion labeling slab, the application of an excessively large B(1) amplitude in combination with adiabatic inversion is recommended to optimize the FAIR perfusion contrast.

Animals↗

PubMed2005

Brain shift estimation in image-guided neurosurgery using 3-D ultrasound.

Intraoperative brain deformation is one of the most important causes affecting the overall accuracy of image-guided neurosurgical procedures. One option for correcting for this deformation is to acquire three-dimensional (3-D) ultrasound data during the operation and use this data to update the information provided by the preoperatively acquired MR data. For 12 patients 3-D ultrasound images have been reconstructed from freehand sweeps acquired during neurosurgical procedures. Ultrasound data acquired prior to and after opening the dura, but prior to surgery, have been quantitatively compared to the preoperatively acquired MR data to estimate the rigid component of brain shift at the first stages of surgery. Prior to opening the dura the average brain shift measured was 3.0 mm parallel to the direction of gravity, with a maximum of 7.5 mm, and 3.9 mm perpendicular to the direction of gravity, with a maximum of 8.2 mm. After opening the dura the shift increased on average 0.2 mm parallel to the direction of gravity and 1.4 mm perpendicular to the direction of gravity. Brain shift can be detected by acquiring 3-D ultrasound data during image-guided neurosurgery. Therefore, it can be used as a basis for correcting image data and preoperative planning for intraoperative deformations.

Algorithms↗

PubMed2005

A trained spin-glass model for grouping of image primitives.

A method is presented that uses grouping to improve local classification of image primitives. The grouping process is based upon a spin-glass system, where the image primitives are treated as possessing a spin. The system is subject to an energy functional consisting of a local and a bilocal part, allowing interaction between the image primitives. Instead of defining the state of lowest energy as the grouping result, the mean state of the system is taken. In this way, instabilities caused by multiple minima in the energy are being avoided. The means of the spins are taken as the a posteriori probabilities for the grouping result. In the paper, it is shown how the energy functional can be learned from example data. The energy functional is defined in such a way that, in case of no interactions between the elements, the means of the spins equal the a priori local probabilities. The grouping process enables the fusion of the a priori local and bilocal probabilities into the a posteriori probabilities. The method is illustrated both on grouping of line elements in synthetic images and on vessel detection in retinal fundus images.

Algorithms↗

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

Resolution-insensitive velocity and flow rate measurement in low-background phase-contrast MRA.

Magnetic resonance (MR) phase-contrast (PC) flow measurements are degraded by partial volume errors when the spatial resolution is low, in particular when a large difference in signal magnitude exists between the fluid and the surrounding material. The latter is often the case in phantom studies and may be encountered when flow is measured in prosthetic vessel segments (such as shunts, grafts, and bypasses) and in contrast-enhanced blood. This paper presents a new method that is designed to measure flow in vessels of circular cross-section with Poiseuille flow and negligible background signal arising from static material around the lumen. The method calculates the average flow velocity directly from the original complex image data by integrating the signal in oppositely velocity-sensitized PC images. The radius is calculated from the summed signal modulus. The method allows accurate and resolution-insensitive measurements of the average flow velocity to be obtained in both cross-sectional and in-plane acquisitions. It is not critical to any of the assumed conditions. The validity and capabilities of the proposed technique are demonstrated by in vitro experiments.

Algorithms↗

PubMed2004

Segmentation of tumors in magnetic resonance brain images using an interactive multiscale watershed algorithm.

RATIONALE AND OBJECTIVE: This article presents the evaluation of an interactive multiscale watershed segmentation algorithm for segmenting tumors in magnetic resonance brain images of patients scheduled for neuronavigational procedures. MATERIALS AND METHODS: The watershed method is compared with manual delineation with respect to accuracy, repeatability, and efficiency. RESULTS: In the 20 patients included in this study, the measured volume of the tumors ranged from 2.7 to 81.9 cm(3). A comparison of the tumor volumes measured with watershed segmentation to the volumes measured with manual delineation shows that the two methods are interchangeable according to the Bland and Altman criterion, and thus equally accurate. The repeatability of the watershed method and the manual method are compared by looking at the similarity of the segmented volumes. The similarity for intraobserver and interobserver variability for watershed segmentation is 96.4% and 95.3%, respectively, compared with 93.5% and 90.0% for manual outlining, from which it may be concluded that the watershed method is more repeatable. Moreover, the watershed algorithm is on average three times faster than manual outlining. CONCLUSION: The watershed method has an accuracy comparable to that of manual delineation and outperforms manual outlining on the criteria of repeatability and efficiency.

Algorithms↗

PubMed2004

Construction and evaluation of an average CT brain image for inter-subject registration.

An average CT brain image is constructed to serve as reference frame for inter-subject registration. A set of 96 clinical CT images is used. Registration includes translation, rotation, and anisotropic scaling. A temporary average based on a subset of 32 images is constructed. This image is used as reference for the iterative construction of the average CT image. This approach is computationally efficient and results in a consistent registration of the 96 images. Registration of new images to the average CT is more consistent than registration to a single CT image. The use of the average CT image is illustrated.

Brain↗

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

The MDF discrimination measure: Fisher in disguise.

Recently, a discrimination measure for feature extraction for two-class data, called the maximum discriminating (MDF) measure (Talukder and Casasent [Neural Networks 14 (2001) 1201-1218]), was introduced. In the present paper, it is shown that the MDF discrimination measure produces exactly the same results as the classical Fisher criterion, on the condition that the two prior probabilities are chosen to be equal. The effect of unequal priors on the efficiency of the measures is also discussed.

Animals↗

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↗

PubMed2004

Ridge-based vessel segmentation in color images of the retina.

A method is presented for automated segmentation of vessels in two-dimensional color images of the retina. This method can be used in computer analyses of retinal images, e.g., in automated screening for diabetic retinopathy. The system is based on extraction of image ridges, which coincide approximately with vessel centerlines. The ridges are used to compose primitives in the form of line elements. With the line elements an image is partitioned into patches by assigning each image pixel to the closest line element. Every line element constitutes a local coordinate frame for its corresponding patch. For every pixel, feature vectors are computed that make use of properties of the patches and the line elements. The feature vectors are classified using a kappaNN-classifier and sequential forward feature selection. The algorithm was tested on a database consisting of 40 manually labeled images. The method achieves an area under the receiver operating characteristic curve of 0.952. The method is compared with two recently published rule-based methods of Hoover et al. and Jiang et al. The results show that our method is significantly better than the two rule-based methods (p < 0.01). The accuracy of our method is 0.944 versus 0.947 for a second observer.

Algorithms↗

PubMed2004

F-information measures in medical image registration.

A measure for registration of medical images that currently draws much attention is mutual information. The measure originates from information theory, but has been shown to be successful for image registration as well. Information theory, however, offers many more measures that may be suitable for image registration. These all measure the divergence of the joint distribution of the images' grey values from the joint distribution that would have been found had the images been completely independent. This paper compares the performance of mutual information as a registration measure with that of other F-information measures. The measures are applied to rigid registration of positron emission tomography (PET)/magnetic resonance (MR) and MR/computed tomography (CT) images, for 35 and 41 image pairs, respectively. An accurate gold standard transformation is available for the images, based on implanted markers. The registration performance, robustness and accuracy of the measures are studied. Some of the measures are shown to perform poorly on all aspects. The majority of measures produces results similar to those of mutual information. An important finding, however, is that several measures, although slightly more difficult to optimize, can potentially yield significantly more accurate results than mutual information.

Algorithms↗

PubMed2004

Suitability of 7 aortic stent-graft models for MRI-based surveillance.

PURPOSE: To evaluate the magnetic resonance imaging (MRI) characteristics of commercially available stent-grafts used for abdominal aortic aneurysm repair. METHODS: Seven endovascular grafts (AneuRx, Lifepath, Talent, Excluder, Zenith, Quantum LP, and Ancure) were suspended in a water bath containing gadolinium and scanned using a 1.5-T clinical MRI scanner. Two different scan techniques (T(1)-weighted spoiled gradient echo and spin echo) based upon a clinical MRI endograft surveillance protocol were used for each stent-graft. The scans were evaluated for susceptibility artifacts and radiofrequency (RF) shielding and caging artifacts. RESULTS: For most endografts, the lumen and structures surrounding the endograft were well visualized. However, the ferromagnetic properties of the Zenith and Lifepath devices resulted in large susceptibly artifacts that obliterated the endograft lumen as well as adjacent structures. All fully supported grafts showed some amount of signal loss from the graft lumen caused by RF caging. For the Ancure graft, evaluation around the attachment sites might be problematic. CONCLUSIONS: An MRI-based surveillance protocol appears to be a viable option for the AneuRx, Talent, Excluder, and Quantum LP stent-grafts.

Aortic Aneurysm, Abdominal↗

PubMed2003

Measuring the arterial input function with gradient echo sequences.

The measurement of the arterial input function by use of gradient echo sequences was investigated by in vitro and in vivo experiments. First, calibration curves representing the influence of the concentration of Gd-DTPA on both the phase and the amplitude of the MR signal were measured in human blood by means of a slow-infusion experiment. The results showed a linear increase in the phase velocity and a quadratic increase in DeltaR(*) (2) as a function of the Gd-DTPA concentration. Next, the resultant calibration curves were incorporated in a partial volume correction algorithm for the arterial input function determination. The algorithm was tested in a phantom experiment and was found to substantially improve the accuracy of the concentration measurement. Finally, the reproducibility of the arterial input function measurement was estimated in 16 patients by considering the input function of the left and the right sides as replicate measurements. This in vivo study showed that the reproducibility of the arterial input function determination using gradient echo sequences is improved by employing a partial volume correction algorithm based on the calibration curve for the contrast agent used.

Algorithms↗