• KOL
    • Nonrigid Image Registration
    • Dirk Loeckx
    • Dirk Loeckx: Influence Statistics

      Dirk Loeckx

      Dirk Loeckx

      icometrix, Leuven, Belgium | IcoMetrix, Leuven, Belgium. | ESAT/PSI-Medical Image Computing & iMinds, KU Leuven, Kasteelpark Arenberg 10 - bus 2441, B-3001, Leuven, Belgium | ...

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      Dirk Loeckx:Expert Impact

      Concepts for whichDirk Loeckxhas direct influence:Nonrigid image registration,Nonrigid registration,Image registration,Pet images,Conditional mutual,Rectal cancer,Temporal subtraction,Myocardial strain.

      Dirk Loeckx:KOL impact

      Concepts related to the work of other authors for whichfor which Dirk Loeckx has influence:Image registration,Giant cell arteritis,Computed tomography,Rectal cancer,Magnetic resonance,Computer assisted,Liver tumor.

      KOL Resume for Dirk Loeckx

      Year
      2016

      icometrix, Leuven, Belgium

      2015

      IcoMetrix, Leuven, Belgium.

      ESAT/PSI-Medical Image Computing & iMinds, KU Leuven, Kasteelpark Arenberg 10 - bus 2441, B-3001, Leuven, Belgium

      2012

      Medical Imaging Research Center, UZ Leuven, Leuven, Belgium

      2011

      Medical Image Computing, Catholic University of Leuven, Leuven, Belgium

      Center for Processing Speech and Images, Department of Electrical Engineering

      2010

      Katholieke Universiteit Leuven, Medical Image Computing, ESAT/PSI, Belgium

      Postdoctoral Fellow of the Research Foundation-Flanders (FWO)

      2009

      Group of Medical Image Computing, Center for Processing Speech and Images

      Medical Image Computing, ESAT/Radiology, Medical Imaging Center, Catholic University Leuven, Leuven, Belgium

      Postdoctoral Fellow of the Research Foundation – Flanders (FWO – Vlaanderen)

      2008

      Department of Electrical Engineering, Medical Image Computing Katholieke Universiteit Leuven, B-3000, Leuven, Belgium

      2007

      From the Departments of Cardiology (J.E., H.H.), Radiology (W.C., S.D., J.B.), and Electrical Engineering (D.L., S.D.B., F.M.), University Hospital Gasthuisberg, University of Leuven, Leuven, Belgium.

      Medical Image Computing, ESAT/PSI, Faculty of Engineering, Katholieke Universiteit Leuven

      2006

      Medical Image Computing (ESAT/PSI), Faculties of Medicine and Engineering, University Hospital Gasthuisberg, Herestraat 49, B-3000, Leuven, Belgium

      2004

      Medical Image Computing (Radiology–ESAT/PSI), Faculties of Medicine and Engineering, University Hospital Gasthuisberg, Herestraat 49, B-3000, Leuven, Belgium

      2003

      Group of Medical Image Computing (Radiology—ESAT/PSI), Faculties of Medicine and Engineering, University Hospital Gasthuisberg, Herestraat 49, B-3000, Leuven, Belgium

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      Sample of concepts for which Dirk Loeckx is among the top experts in the world.
      Concept World rank
      radiation oncologist displacements #1
      proposed considerations ptv #1
      thoraco‐abdominal radiosurgery #1
      marker sampling #1
      multiple scans representative #1
      nonrigid image registration #1
      walled univentricular #2
      stiff inclusions method #2
      threedimensional cardiac motion #2
      subsequent volumes #2
      validation regional level #2
      predicted apexbase gradients #2
      univentricular phantoms #2
      inclusions 17mm #2
      validation regional #2
      sonomicrometry radial #2
      univentricular thick #2
      drift εrr #3
      coordinate systems respect #3
      sonomicrometry εrr #3
      observation lesion evolution #3
      εll absolute error #3
      confounding inhomogeneity #3
      paper confounding #3
      principal diagonalization #3
      calculation directions #3
      reduction subtraction #3
      cardiac coordinate systems #3
      systems average position #3
      εll #3
      inhomogeneity image registration #3
      images boundary conditions #3
      correction image registration #3
      order unwanted deformations #3
      strain values principal #3
      fixed point correspondences #3
      subtle interactions methods #3
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      Prominent publications by Dirk Loeckx

      KOL-Index: 13362

      PURPOSE: The purpose of this study is to investigate the use of PET/CT with fluorodeoxyglucose (FDG), fluorothymidine (FLT) and fluoromisonidazole (FMISO) for radiotherapy (RT) target definition and evolution in rectal cancer.

      MATERIALS AND METHODS: PET/CT was performed before and during preoperative chemoradiotherapy (CRT) in 15 patients with resectable rectal cancer. PET signals were delineated and CT images on the different time points were non-rigidly registered. Mismatch analyses ...

      Known for Rectal Cancer | Fdg Pet | Preoperative Chemoradiotherapy | Time Points | 15 Patients
      KOL-Index: 11008

      OBJECTIVE: GCA carries an increased risk of developing thoracic aortic aneurysms. Previous work with fluorodeoxyglucose (FDG)-PET has shown that the aorta is frequently involved in this type of vasculitis. We wanted to investigate whether there is a correlation between the extent of vascular FDG uptake during the acute phase of GCA and the aortic diameter at late follow-up.

      METHODS: All patients with biopsy-proven GCA who ever underwent an FDG-PET scan in our centre were asked to undergo ...

      Known for Thoracic Aorta | Aortic Diameter | Large Vessels | Cell Arteritis | Diagnosis Gca
      KOL-Index: 9093

      GPR39, which may function as a Zn(2+) sensor, is a member of the G protein-coupled receptor family that also includes the receptor for the hunger hormone ghrelin. The down-regulation of GPR39 mRNA in adipose tissue of obese type 2 diabetic patients suggests that GPR39 may contribute to the pathogenesis of the disease. The present study aimed to investigate the role of GPR39 in the regulation of energy balance and glucose homeostasis in wild-type (GPR39(+/+) ) and GPR39 knockout mice ...

      Known for Glucose Homeostasis | Ghrelin Receptor | Mice Hfd | Role Gpr39 | Mouse Model
      KOL-Index: 7994

      PURPOSE: To investigate the feasibility of integrating multiple imaging modalities for image-guided radiotherapy in rectal cancer.

      PATIENTS AND METHODS: Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were performed before, during, and after preoperative chemoradiotherapy (CRT) in patients with resectable rectal cancer. The FDG-PET signals were segmented with an adaptive threshold-based and a gradient-based method. ...

      Known for Rectal Cancer | Fdg Pet | Guided Radiotherapy | Resonance Imaging | Positron Emission
      KOL-Index: 7553

      Current ultrasound methods for measuring myocardial strain are often limited to measurements in one or two dimensions. Cardiac motion and deformation however are truly 3-D. With the introduction of matrix transducer technology, 3-D ultrasound imaging of the heart has become feasible but suffers from low temporal and spatial resolution, making 3-D strain estimation challenging. In this paper, it is shown that automatic intensity-based spatio-temporal elastic registration of currently ...

      Known for Ultrasound Images | Feasibility Study | Strain Estimation | Dimensional Cardiac | Absolute Error
      KOL-Index: 7233

      INTRODUCTION: Patient respiration influences the accuracy of image integration approaches used during atrial fibrillation (AF) ablation procedures. We assessed both absolute and relative changes in left atrial (LA) and pulmonary venous (PV) anatomy due to respiration and their implications for 3D image integration.

      METHODS AND RESULTS: Intensity-based segmentation of the LA and PVs was performed on cardiac computed tomography (CT) images obtained during both inspiration and expiration in ...

      Known for Image Integration | Atrial Fibrillation | Respiratory Motion | Computer Assisted | Computed Tomography
      KOL-Index: 6825

      BACKGROUND: [18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET) is a valuable tool for monitoring response to therapy in oncology. In longitudinal studies, however, patients are not scanned in exactly the same position. Rigid and non-rigid image registration can be applied in order to reuse baseline volumes of interest (VOI) on consecutive studies of the same patient. The purpose of this study was to investigate the impact of various image registration strategies ...

      Known for Image Registration | Suvmean Tlg | Pet Scans | Baseline Volumes | Positron Emission Tomography
      KOL-Index: 6646

      EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms ...

      Known for Registration Methods | Empire10 Challenge | Thoracic Image | Reliable Assessment | New Participants
      KOL-Index: 6492

      In this paper, a specific method is presented to facilitate the semi-automatic segmentation of liver tumors and liver metastases in CT images. Accurate and reliable segmentation of tumors is essential for the follow-up of cancer treatment. The core of the algorithm is a level set method. The initialization is generated by a spiral-scanning technique based on dynamic programming. The level set evolves according to a speed image that is the result of a statistical pixel classification ...

      Known for Liver Tumors | Specificity Tomography | Level Method | Radiographic Image | Manual Delineations
      KOL-Index: 6355

      Maximization of mutual information (MMI) is a popular similarity measure for medical image registration. Although its accuracy and robustness has been demonstrated for rigid body image registration, extending MMI to nonrigid image registration is not trivial and an active field of research. We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. cMI starts from a 3-D joint histogram incorporating, besides the intensity dimensions, also ...

      Known for Nonrigid Image Registration | Conditional Mutual | Image Intensities | Spatial Distribution | Accuracy Robustness
      KOL-Index: 6319

      A new generic model-based segmentation algorithm is presented, which can be trained from examples akin to the active shape model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Whereas ASM alternates between shape and intensity information during search, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark ...

      Known for Sensitivity Specificity | Anatomical Structures | Image Segmentation | Dynamic Programming | Adjacent Landmarks
      KOL-Index: 5912

      We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. We start from a 3D joint histogram incorporating, besides the reference and floating intensity dimensions, also a spatial dimension expressing the location of the joint intensity pair in the reference image. cMI is calculated as the expectation value of the conditional mutual information between the reference and floating intensities given the spatial distribution.Validation ...

      Known for Conditional Mutual | Nonrigid Image Registration | Computerassisted Imaging | Automated Reproducibility | Spatial Dimension
      KOL-Index: 5303

      Voxel-based nonrigid image registration can be formulated as an optimisation problem whose goal is to minimise a cost function, consisting of a first term that characterises the similarity between both images and a second term that regularises the transformation and/or penalties improbable or impossible deformations. Within this paper, we extend previous works on nonrigid image registration by the introduction of a new penalty term that expresses the local rigidity of the deformation. A ...

      Known for Nonrigid Image Registration | Local Rigidity | Penalty Term | Cost Function | Proposed Constraint
      KOL-Index: 5112

      RATIONALE AND OBJECTIVES: Computed tomography angiography (CTA) is an established tool for vascular imaging. However, high-intensity nonvascular structures in the contrast image can seriously hamper luminal visualization. This is an issue for three-dimensional visualization, where high-intensity structures might cover the underlying vasculature. But also in two dimensions, calcified plaques adjacent to the contrast-enhanced vessel lumen impede correct determination of the vessel ...

      Known for Nonrigid Registration | Contrast Image | Subtraction Angiography | Carotid Arteries | Imaging Dimensional
      KOL-Index: 5028

      Research has raised a growing concern about the accuracy of rescaled generic musculoskeletal models for estimating a subject's musculoskeletal geometry. Information extracted from magnetic resonance (MR) images can improve the subject-specific detail and accuracy of musculoskeletal models. Nevertheless, methods that allow efficient, automated definition of subject-specific muscular models for use in biomechanical analysis of gait have not yet been published to the best of our knowledge. ...

      Known for Muscle Models | Image Registration | Magnetic Resonance | Lower Limb | Visual Inspection

      Key People For Nonrigid Image Registration

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      icometrix, Leuven, Belgium | IcoMetrix, Leuven, Belgium. | ESAT/PSI-Medical Image Computing & iMinds, KU Leuven, Kasteelpark Arenberg 10 - bus 2441, B-3001, Leuven, Belgium | Medical Imaging Research Center, UZ Leuven, Leuven, Belgium | Metrix NV, Be

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