K. Leemput

发表

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Brian B. Avants, D. Louis Collins, Hervé Delingette, 2015, IEEE Transactions on Medical Imaging.

Joint segmentation via patient-specific latent anatomy model

Bjoern H Menze, P. Golland, N. Ayache, 2009 .

Segmenting Glioma in Multi-Modal Images using a Generative Model for Brain Lesion Segmentation

D. Lashkari, P. Golland, N. Ayache, 2012 .

Automatic Brain and Tumor Segmentation 1

G. Gerig, E. Bullitt, K. Leemput, 2002 .

SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution pdf

Axel Thielscher, Bruce Fischl, Juan Eugenio Iglesias, 2021, ArXiv.

Sequence analysis Prediction of kinase-specific phosphorylation sites using conditional random fields

A. Verschoren, K. Leemput, K. Laukens, 2008 .

Model-Based Brain Tissue Classification

Siddharth Srivastava, F. Maes, D. Vandermeulen, 2005 .

An Inference Language for Imaging

Koenraad Van Leemput, Ciprian Catana, Stefano Pedemonte, 2014, BAMBI.

Development and Application of Tools for MRI Analysis - A Study on the Effects of Exercise in Patients with Alzheimer's Disease and Generative Models for Bias Field Correction in MR Brain Imaging

K. Leemput, C. Larsen, 2016 .

PD-0593: The impact of a Dixon sequence in creating a pseudo CT scan from MR images using a Gaussian mixture regression model

K. Leemput, J. Edmund, R. H. Hansen, 2013 .

Subjects With Intellectual Disability and Familial Need for Full-Time Special Education Show Regional Brain Alterations: A Voxel-Based Morphometry Study

T. Autti, K. Leemput, R. Raininko, 2009, Pediatric Research.

Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer – ASEG and SAMSEG

Adrian V. Dalca, J. E. Iglesias, D. Greve, 2020, NeuroImage.

Supervised Nonparametric Image Parcellation Citation Sabuncu

Polina, B. Fischl, M. Sabuncu, 2010 .

Nonparametric mixture models for supervised image parcellation Citation

P. Golland, B. Fischl, M. Sabuncu, 2010 .

Surface-based mapping of the serotonin transporter binding in cerebral cortex-filtering and modeling of PET / MRI data

C. Svarer, K. Leemput, Mikael Agn, 2013 .

A Learning Strategy for Contrast-agnostic MRI Segmentation pdf

Bruce Fischl, Douglas Greve, Juan Eugenio Iglesias, 2020, MIDL.

SP-0510: Dose planning based on MRI as the sole modality: Why, how and when?

Hans Martin Kjer, Jens M. Edmund, Daniel Andreasen, 2015 .

PSACNN: Pulse Sequence Resilient Fast Whole Brain Segmentation

Amod Jog, Bruce Fischl, Koen Van Leemput, 2019 .

An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation

D. Greve, H. Siebner, H. Lundell, 2022, ArXiv.

3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology (Accepted at MICCAI 2020)

Adrian V. Dalca, J. E. Iglesias, Henry F. J. Tregidgo, 2020 .

MR brain image segmentation using the EM algorithm

Paul Suetens, Dirk Vandermeulen, Frederik Maes, 2001 .

Validation of nonlinear filtering to improve tissue segmentation in MR images of the brain

Paul Suetens, Dirk Vandermeulen, Frederik Maes, 2001 .

A generator of biologically plausible synthetic gene expression data for design and analysis of structure learning algorithms

Kathleen Marchal, Bart De Moor, Koenraad Van Leemput, 2005 .

High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas

B Fischl, J. E. Iglesias, Z. M Saygin, 2017, NeuroImage.

SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining

Світлана Миколаївна Ефендієва, J. E. Iglesias, D. Greve, 2023 .

PSACNN: Pulse sequence adaptive fast whole brain segmentation

Amod Jog, Koenraad Van Leemput, Bruce Fischl, 2019, NeuroImage.

3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology

Bruce Fischl, Juan Eugenio Iglesias, Adrian V. Dalca, 2020, MICCAI.

Accurate and robust whole-head segmentation from magnetic resonance images for individualized head modeling

Koenraad Van Leemput, Hartwig R. Siebner, Kristoffer Hougaard Madsen, 2020, NeuroImage.

A Learning Strategy for Contrast-agnostic MRI Segmentation

Adrian V. Dalca, J. E. Iglesias, D. Greve, 2020, MIDL.

Joint inference on structural and diffusion MRI for sequence-adaptive Bayesian segmentation of thalamic nuclei with probabilistic atlases

Koenraad Van Leemput, Polina Golland, Juan Eugenio Iglesias, 2019, IPMI.

A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

André J. W. van der Kouwe, Koenraad Van Leemput, Martina Bocchetta, 2018, NeuroImage.

Skull segmentation from MR scans using a higher-order shape model based on convolutional restricted Boltzmann machines

Koenraad Van Leemput, Hartwig R. Siebner, Kristoffer Hougaard Madsen, 2018, Medical Imaging.

Fast and sequence-adaptive whole-brain segmentation using parametric Bayesian modeling

Koenraad Van Leemput, Juan Eugenio Iglesias, Oula Puonti, 2016, NeuroImage.

Bayesian longitudinal segmentation of hippocampal substructures in brain MRI using subject-specific atlases

Koenraad Van Leemput, Bruce Fischl, Juan Eugenio Iglesias, 2016, NeuroImage.

Bayesian segmentation of brainstem structures in MRI

Norbert Schuff, Koenraad Van Leemput, Bruce Fischl, 2015, NeuroImage.

N3 Bias Field Correction Explained as a Bayesian Modeling Method

Koenraad Van Leemput, Juan Eugenio Iglesias, Christian Thode Larsen, 2014, BAMBI.

A unified framework for cross-modality multi-atlas segmentation of brain MRI

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2013, Medical Image Anal..

Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2013, Medical Image Anal..

Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models

Koenraad Van Leemput, Juan Eugenio Iglesias, Oula Puonti, 2013, MICCAI.

Is Synthesizing MRI Contrast Useful for Inter-modality Analysis?

Ben Glocker, Koenraad Van Leemput, Ender Konukoglu, 2013, MICCAI.

A Generative Model for Probabilistic Label Fusion of Multimodal Data

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2012, MBIA.

Incorporating Parameter Uncertainty in Bayesian Segmentation Models: Application to Hippocampal Subfield Volumetry

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2012, MICCAI.

The Relevance Voxel Machine (RVoxM): A Self-Tuning Bayesian Model for Informative Image-Based Prediction

Mert R. Sabuncu, Koenraad Van Leemput, M. Sabuncu, 2012, IEEE Transactions on Medical Imaging.

A generative model for multi-atlas segmentation across modalities

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

A Generative Model for Image Segmentation Based on Label Fusion

Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Leemput, 2010, IEEE Transactions on Medical Imaging.

Segmentation of image ensembles via latent atlases

Koenraad Van Leemput, Polina Golland, William M. Wells, 2010, Medical Image Anal..

Joint Segmentation of Image Ensembles via Latent Atlases

Koenraad Van Leemput, Polina Golland, William M. Wells, 2009, MICCAI.

Supervised Nonparametric Image Parcellation

Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Leemput, 2009, MICCAI.

Encoding Probabilistic Brain Atlases Using Bayesian Inference

Koen Van Leemput, K. Leemput, K. V. Leemput, 2009, IEEE Transactions on Medical Imaging.

Model-Based Segmentation of Hippocampal Subfields in Ultra-High Resolution In Vivo MRI

Koenraad Van Leemput, Polina Golland, Lawrence L. Wald, 2008, MICCAI.

Probabilistic Brain Atlas Encoding Using Bayesian Inference

Koenraad Van Leemput, K. Leemput, K. V. Leemput, 2006, MICCAI.

A Statistical Framework for Partial Volume Segmentation

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 2001, MICCAI.

Automated model-based bias field correction of MR images of the brain

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 1999, IEEE Transactions on Medical Imaging.

Automated model-based tissue classification of MR images of the brain

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 1999, IEEE Transactions on Medical Imaging.

SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution

J. E. Iglesias, D. Greve, B. Fischl, 2021, ArXiv.

JNCL patients show marked brain volume alterations on longitudinal MRI in adolescence

T. Autti, K. Leemput, M. Mannerkoski, 2008, Journal of Neurology.

Quantitative analysis of signal abnormalities in MR imaging for multiple sclerosis and creutzfeldt-jakob disease

Koen Van Leemput, K. Leemput, K. V. Leemput, 2001 .

Automated segmentation of multiple sclerosis lesions by model outlier detection

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 2001, IEEE Transactions on Medical Imaging.

Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images pdf

Ian Law, Stefano Cerri, Koen Van Leemput, 2021, Scientific Reports.

SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms

Kathleen Marchal, Bart De Moor, Koenraad Van Leemput, 2006, BMC Bioinformatics.

Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration pdf

Panagiotis Angelikopoulos, Koenraad Van Leemput, Petros Koumoutsakos, 2018, ArXiv.

SYSTEMATIC COMPARISON OF DIFFERENT TECHNIQUES TO MEASURE HIPPOCAMPAL SUBFIELD VOLUMES IN ADNI2

Michael W. Weiner, Paul A. Yushkevich, Lei Wang, 2016, Alzheimer's & Dementia.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

Koenraad Van Leemput, Lawrence L. Wald, Bruce Fischl, 2015, NeuroImage.

Prediction of MGMT Methylation Status of Glioblastoma using Radiomics and Latent Space Shape Features pdf

Stefano Cerri, Koen Van Leemput, Sveinn P'alsson, 2021, BrainLes@MICCAI.

Quantitative MR Imaging

Dirk Vandermeulen, Koen Van Leemput, Frederik Maes, 2001 .

Quantification of Cerebral Grey and White Matter Asymmetry from MRI

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 1999, MICCAI.

Predicting the location of entorhinal cortex from MRI

Bruce R. Rosen, André J. W. van der Kouwe, P. Ellen Grant, 2009, NeuroImage.

Predicting the location of human perirhinal cortex, Brodmann's area 35, from MRI

André J. W. van der Kouwe, Koenraad Van Leemput, Lawrence L. Wald, 2013, NeuroImage.

The Relevance Voxel Machine (RVoxM): A Bayesian Method for Image-Based Prediction

Mert R. Sabuncu, Koenraad Van Leemput, M. Sabuncu, 2011, MICCAI.

Mild cognitive impairment: Differential atrophy in the hippocampal subfields

X Seron, M. Kavec, C. Grandin, 2011, Alzheimer's & Dementia.

Joint Segmentation Of Multiple Sclerosis Lesions And Brain Anatomy In MRI Scans Of Any Contrast And Resolution With CNNs

Juan Eugenio Iglesias, Adrian V. Dalca, Benjamin Billot, 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

A unifying framework for partial volume segmentation of brain MR images

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 2003, IEEE Transactions on Medical Imaging.

Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2012

Bjoern H. Menze, Bjoern H Menze, Marcel Prastawa, 2012 .

An algorithm for optimal fusion of atlases with different labeling protocols

Mert R. Sabuncu, Koenraad Van Leemput, Bruce Fischl, 2015, NeuroImage.

A Probabilistic, Non-parametric Framework for Inter-modality Label Fusion

Mert R. Sabuncu, Koenraad Van Leemput, Juan Eugenio Iglesias, 2013, MICCAI.

An automatically generated texture-based atlas of the lungs

Koenraad Van Leemput, Henning Müller, Yashin Dicente Cid, 2018, Medical Imaging.

A Generative Model for Brain Tumor Segmentation in Multi-Modal Images

Nicholas Ayache, Koenraad Van Leemput, Polina Golland, 2010, MICCAI.

SynthSeg: Domain Randomisation for Segmentation of Brain MRI Scans of any Contrast and Resolution

Adrian V. Dalca, J. E. Iglesias, D. Greve, 2021, ArXiv.

Prediction of kinase-specific phosphorylation sites using conditional random fields

Koenraad Van Leemput, Thanh Hai Dang, Kris Laukens, 2008, Bioinform..

Asymmetric Image-Template Registration

Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Leemput, 2009, MICCAI.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, 2305.08992.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, 2305.09011.

Model-based brain and tumor segmentation

Guido Gerig, Koenraad Van Leemput, Elizabeth Bullitt, 2002, Object recognition supported by user interaction for service robots.

A modality‐adaptive method for segmenting brain tumors and organs‐at‐risk in radiation therapy planning

John Ashburner, Koen Van Leemput, Oula Puonti, 2018, Medical Image Anal..

Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape

Koenraad Van Leemput, Ian Law, Oula Puonti, 2015, Brainles@MICCAI.

Semi-Supervised Variational Autoencoder for Survival Prediction

K. Leemput, Andrea Dittadi, Stefano Cerri, 2019, BrainLes@MICCAI.

A Generative Approach for Image-Based Modeling of Tumor Growth

Antti Honkela, Nicholas Ayache, Koenraad Van Leemput, 2011, IPMI.

An open-source tool for longitudinal whole-brain and white matter lesion segmentation

D. Greve, H. Siebner, H. Lundell, 2022, NeuroImage: Clinical.

A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

Douglas N. Greve, Koen Van Leemput, Andrew Hoopes, 2020, MLCN/RNO-AI@MICCAI.

A contrast-adaptive method for simultaneous whole-brain and lesion segmentation in multiple sclerosis

Koenraad Van Leemput, Mark Mühlau, Jens Wuerfel, 2020, NeuroImage.

Encoding Probabilistic Brain Atlases

Koen Van Leemput, K. Leemput, K. V. Leemput, 2009 .

Automatic Brain and Tumor Segmentation

Guido Gerig, Koenraad Van Leemput, Elizabeth Bullitt, 2002, MICCAI.

Relevance Vector Machines for Harmonization of MRI Brain Volumes Using Image Descriptors

Koenraad Van Leemput, Ezequiel de la Rosa, Diana Maria Sima, 2019, OR/MLCN@MICCAI.

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation— With Application to Tumor and Stroke

Gábor Székely, Koenraad Van Leemput, Polina Golland, 2016, IEEE Transactions on Medical Imaging.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, ArXiv.

Automated Segmentation of MS Lesions from Multi-channel MR Images

Koenraad Van Leemput, Paul Suetens, Fernando Bello, 1999, MICCAI.

A Lightweight Causal Model for Interpretable Subject-level Prediction

O. Puonti, K. Leemput, C. Mauri, 2023, ArXiv.

A contrast-adaptive method for simultaneous whole-brain and lesion segmentation in multiple sclerosis

Koenraad Van Leemput, Mark Mühlau, Hartwig R. Siebner, 2020, NeuroImage.

Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

Koenraad Van Leemput, Oula Puonti, O. Puonti, 2015, Brainles@MICCAI.

Automatic Segmentation of Brain Tissues and MR Bias Field Correction Using a Cigital Brain Atlas

Koenraad Van Leemput, Paul Suetens, Dirk Vandermeulen, 1998, MICCAI.

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, ArXiv.

Validating module network learning algorithms using simulated data

Kathleen Marchal, Yvan Saeys, Koenraad Van Leemput, 2007, BMC Bioinformatics.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, ArXiv.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Bjoern H Menze, J. E. Iglesias, Walter F. Wiggins, 2023, ArXiv.

Collaboration for a systematic comparison of different techniques to measure subfield volumes: Announcement and first results

Lei Wang, Juan Eugenio Iglesias, Michael Weiner, 2013, Alzheimer's & Dementia.

Multi-modal Brain Tumor Segmentation via Latent Atlases

Bjoern H. Menze, Bjoern H Menze, Tammy Riklin Raviv, 2012 .

SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms

B. Moor, B. Naudts, K. Marchal, 2005, BMC Bioinformatics.

Validating module network learning algorithms using simulated data

Y. Saeys, Steven Maere, M. Kuiper, 2007, BMC Bioinformatics.

Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data

Kathleen Marchal, Bart De Moor, Koenraad Van Leemput, 2008, Artificial Life.