Medical Imaging Research Center

Leuven, Belgium

Medical Imaging Research Center

Leuven, Belgium
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Wouters A.,Catholic University of Leuven | Wouters A.,University Hospital Leuven | Wouters A.,Medical Imaging Research Center | Lemmens R.,Catholic University of Leuven | And 7 more authors.
Frontiers in Neurology | Year: 2014

Patients, who wake up with an ischemic stroke, account for a large number of the total stroke population, due to circadian morning predominance of stroke. Currently, this subset of patients is excluded from revascularization-therapy since no exact time of onset is known. A large group of these patients might be eligible for therapy. In this review, we assessed the current literature about the hypothesis that wake-up-strokes occur just prior on awakening and if this subgroup differs in characteristics compared to the overall stroke population. We looked at the safety and efficacy of thrombolysis and interventional techniques in the group of patients with unknown stroke-onset. We performed a meta-analysis of the diagnostic accuracy of the diffusion-FLAIR mismatch in identifying stroke within 3 and 4.5 h. The different imaging-selection criteria that can be used to treat these patients are discussed. Additional research on imaging findings associated with recent stroke and penumbral imaging will eventually lead to a shift from a rigid time-frame based therapy to a tissue-based individualized treatment approach. © 2014 Wouters, Lemmens, Dupont and Thijs.

Salvagnini E.,Medical Imaging Research Center | Bosmans H.,Medical Imaging Research Center | Struelens L.,SCK | Marshall N.W.,Medical Imaging Research Center
Medical Physics | Year: 2013

Purpose: The aim of this paper was to illustrate the value of the new metric effective detective quantum efficiency (eDQE) in relation to more established measures in the optimization process of two digital mammography systems. The following metrics were included for comparison against eDQE: detective quantum efficiency (DQE) of the detector, signal difference to noise ratio (SdNR), and detectability index (d′) calculated using a standard nonprewhitened observer with eye filter. Methods: The two systems investigated were the Siemens MAMMOMAT Inspiration and the Ho-logic Selenia Dimensions. The presampling modulation transfer function (MTF) required for the eDQE was measured using two geometries: a geometry containing scattered radiation and a low scatter geometry. The eDQE, SdNR, and d′ were measured for poly(methyl methacrylate) (PMMA) thicknesses of 20, 40, 60, and 70 mm, with and without the antiscatter grid and for a selection of clinically relevant target/filter (T/F) combinations. Figures of merit (FOMs) were then formed from SdNR and d′ using the mean glandular dose as the factor to express detriment. Detector DQE was measured at energies covering the range of typical clinically used spectra. Results: The MTF measured in the presence of scattered radiation showed a large drop at low spatial frequency compared to the low scatter method and led to a corresponding reduction in eDQE. The eDQE for the Siemens system at 1 mm -1 ranged between 0.15 and 0.27, depending on T/F and grid setting. For the Hologic system, eDQE at 1 mm-1 varied from 0.15 to 0.32, again depending on T/F and grid setting. The eDQE results for both systems showed that the grid increased the system efficiency for PMMA thicknesses of 40 mm and above but showed only small sensitivity to T/F setting. While results of the SdNR and d′ based FOMs confirmed the eDQE grid position results, they were also more specific in terms of T/F selection. For the Siemens system at 20 mm PMMA, the FOMs indicated Mo/Mo (grid out) as optimal while W/Rh (grid in) was the optimal configuration at 40, 60, and 70 mm PMMA. For the Hologic, the FOMs pointed to W/Rh (grid in) at 20 and 40 mm of PMMA while W/Ag (grid in) gave the highest FOM at 60 and 70 mm PMMA. Finally, DQE at 1 mm-1 averaged for the four beam qualities studied was 0.44 ± 0.02 and 0.55 ± 0.03 for the Siemens and Hologic detectors, respectively, indicating only a small influence of energy on detector DQE. Conclusions: Both the DQE and eDQE data showed only a small sensitivity to T/F setting for these two systems. The eDQE showed clear preferences in terms of scatter reduction, being highest for the grid-in geometry for PMMA thicknesses of 40 mm and above. The SdNR and d′ based figures of merit, which contain additional weighting for contrast and dose, pointed to specific T/F settings for both systems. © 2013 American Association of Physicists in Medicine.

Claes P.,Medical Imaging Research Center | Claes P.,University of Melbourne | Walters M.,Princess Margaret Hospital for Children | Clement J.,University of Melbourne
International Journal of Oral and Maxillofacial Surgery | Year: 2012

The capacity to process three-dimensional facial surfaces to objectively assess outcomes of craniomaxillofacial care is urgently required. Available surface registration techniques depart from conventional facial anthropometrics by not including anatomical relationship in their analysis. Current registrations rely on the manual selection of areas or points that have not moved during surgery, introducing subjectivity. An improved technique is proposed based on the concept of an anthropometric mask (AM) combined with robust superimposition. The AM is the equivalent to landmark definitions, as used in traditional anthropometrics, but described in a spatially dense way using (∼10.000) quasi-landmarks. A robust superimposition is performed to align surface images facilitating accurate measurement of spatial differences between corresponding quasi-landmarks. The assessment describes magnitude and direction of change objectively and can be displayed graphically. The technique was applied to three patients, without any modification and prior knowledge: a 4-year-old boy with Treacher-Collins syndrome in a resting and smiling pose; surgical correction for hemimandibular hypoplasia; and mandibular hypoplasia with staged orthognathic procedures. Comparisons were made with a reported closest-point (CP) strategy. Contrasting outcomes were found where the CP strategy resulted in anatomical implausibility whilst the AM technique was parsimonious to expected differences. © 2011 International Association of Oral and Maxillofacial Surgeons.

Monnin P.,University of Lausanne | Bosmans H.,Medical Imaging Research Center | Verdun F.R.,University of Lausanne | Marshall N.W.,Medical Imaging Research Center
Physics in Medicine and Biology | Year: 2014

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 μGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed. Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure. © 2014 Institute of Physics and Engineering in Medicine.

Geethanath S.,Medical Imaging Research Center | Reddy R.,Medical Imaging Research Center | Konar A.S.,Medical Imaging Research Center | Imam S.,Medical Imaging Research Center | And 3 more authors.
Critical Reviews in Biomedical Engineering | Year: 2013

Compressed sensing (CS) is a mathematical framework that reconstructs data from highly undersampled measurements. To gain acceleration in acquisition time, CS has been applied to MRI and has been demonstrated on diverse MRI methods. This review discusses the important requirements to qualify MRI to become an optimal application of CS, namely, sparsity, pseudo-random undersampling, and nonlinear reconstruction. By utilizing concepts of transform sparsity and compression, CS allows acquisition of only the important coefficients of the signal during the acquisition. A priori knowledge of MR images specifically related to transform sparsity is required for the application of CS. In this paper, Section I introduces the fundamentals of CS and the idea of CS as applied to MRI. The requirements for application of CS to MRI is discussed in Section II, while the various acquisition techniques, reconstruction techniques, the advantages of combining CS and parallel imaging, and sampling mask design problems are discussed in Section III. Numerous applications of CS in MRI due to its ability to improve imaging speed are reviewed in section IV. Clinical evaluations of some of the CS applications recently published are discussed in Section V. Section VI provides information on available open source software that could be used for CS implementations. © 2013 by Begell House, Inc.

Bickell M.G.,Medical Imaging Research Center | Zhou L.,Medical Imaging Research Center | Nuyts J.,Medical Imaging Research Center
IEEE Nuclear Science Symposium Conference Record | Year: 2013

A spatially variant resolution modelling technique is presented which estimates the system matrix on-the-fly. The method randomly redistributes the line-of-response endpoints according to probability density functions describing the detector response and photon acollinearity effects. A list-mode OSEM algorithm is used for the reconstruction. We demonstrate that this model agrees with measured PSFs and we present results showing an improvement in resolution recovery as compared to using a Gaussian convolution to model the resolution, although with an increase in noise. We also present results from applying this method to event-by-event rigid motion correction with list-mode reconstruction using the microPET Focus220 scanner. © 2013 IEEE.

Mouton A.,Cranfield University | Megherbi N.,Cranfield University | Van Slambrouck K.,Medical Imaging Research Center | Nuyts J.,Medical Imaging Research Center | Breckon T.P.,Cranfield University
2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings | Year: 2013

This paper presents an extension to a recent intensity-limiting sino-gram completion-based Metal Artefact Reduction (MAR) algorithm for Computed Tomography (CT) images containing multiple metal objects. A novel weighting scheme is introduced, whereby the intensities of the MAR-corrected pixels are modified based on their spatial locations relative to the metal objects. Pixels falling within the straight-line regions connecting multiple metal objects are subjected to less intensive intensity-limiting, thereby compensating for the characteristic dark bands occurring in these regions. Extensive experimentation is performed on a state-of-the-art numerical simulation, a clinical CT data set and a baggage security CT data set. Comprehensive performance analysis, using reference and reference-free error metrics, Bland-Altman plots and visual comparisons, demonstrate an improvement in the restoration of the underestimated intensities occurring in the regions connecting multiple metal objects. © 2013 IEEE.

PubMed | Pennsylvania State University, Catholic University of Leuven and Medical Imaging Research Center
Type: | Journal: BioMed research international | Year: 2017

The craniofacial complex is the billboard of sorts containing information about sex, health, ancestry, kinship, genes, and environment. A thorough knowledge of the genes underlying craniofacial morphology is fundamental to understanding craniofacial biology and evolution. These genes can also provide an important foundation for practical efforts like predicting faces from DNA and phenotype-based facial diagnostics. In this work, we focus on the various sources of knowledge regarding the genes that affect patterns of craniofacial development. Although tremendous successes recently have been made using these sources in both methodology and biology, many challenges remain. Primary among these are precise phenotyping techniques and efficient modeling methods.

George J.,Medical Imaging Research Center
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention | Year: 2012

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has become the de facto standard for current clinical therapy follow up evaluations. In pursuit of robust biomarkers for predicting early therapy response, an efficient marker quantification procedure is certainly a necessity. Among various PET derived markers, the clinical investigations indicated that the total lesion metabolic activity (TLA) of a tumor lesion has a good prognostic value in several longitudinal studies. We utilize a fuzzy multi-class modeling using a stochastic expectation maximization (SEM) algorithm to fit a finite mixture model (FMM) to the PET image. We then propose a direct estimation formula for TLA and SUVmean from this multi-class statistical model. In order to evaluate our proposition, a realistic liver lesion is simulated and reconstructed. All results were evaluated with reference to the ground truth knowledge. Our experimental study conveys that the proposed method is robust enough to handle background heterogeneities in realistic scenarios.

PubMed | Medical Imaging Research Center
Type: | Journal: European heart journal | Year: 2017

Sudden cardiac death (SCD) is a complex phenomenon, occurring either in apparently normal individuals or in those where there is a recognized underlying cardiac abnormality. In both groups, the lethal arrhythmia has frequently been related to the physiologic trigger of either exercise or stress. Prior research into SCD has focused mainly on a combination of identifying either vulnerable myocardial substrates; pharmacological approaches to altering electrical activation/repolarisation in substrates; or the suppression of induced lethal arrhythmias with implantable defibrillators. However, it has been suggested that in a significant number of cases, the interaction of a transient induced trigger with a pre-existing electrical or mechanical substrate is the basis for the induction of the sustained lethal arrhythmia. In this manuscript we will discuss the precise mechanisms whereby one of such potential physiologic trigger: an acute change in systolic blood pressure, can induce a sequence of alterations in global and local cardiac mechanics which in turn result in regional left ventricular post-systolic deformation which, mediated (through stretch-induced changes in local mechano-electrical coupling) provokes local electrical after-depolarisations which can spill over into complex runs of premature ventricular beats. These local acute pressure/stretch induced runs of ventricular ectopy originate in either basal or apical normal myocardium and, in combination with a co-existing distal pro-arrhymic substrate, can interact to induce a lethal arrhythmia.

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