default search action
Pierrick Bourgeat
Pierrick T. Bourgeat
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
- [j25]Martin Saint-Jalmes
, Victor Fedyashov, Daniel Beck
Disease progression modelling of Alzheimer's disease using probabilistic principal components analysis. NeuroImage 278: 120279 (2023) - [j24]Ariane Bollack
Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies. NeuroImage 280: 120313 (2023) - [c67]Léo Lebrat
Generalization Properties of Geometric 3D Deep Learning Models for Medical Segmentation. ISBI 2023: 1-5 - [c66]Filip Rusak, Rodrigo Santa Cruz, Hilda Chourak, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
When to Use Augmentation - Variability Insufficient for Cortical Thickness Estimation Improvement. ISBI 2023: 1-5 - [c65]Julie Trinder, Pierrick Bourgeat, Ying Xia, Jurgen Fripp
An Informatics Platform for the Management of Data for Australian Dementia Network (ADNeT) Initiative. MedInfo 2023: 1364-1365 - [c64]Joshua Peters, Léo Lebrat
DBCE : A Saliency Method for Medical Deep Learning Through Anatomically-Consistent Free-Form Deformations. WACV 2023: 1958-1968 - 2022
- [j23]Filip Rusak
Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods. Medical Image Anal. 82: 102576 (2022) - [j22]Pierrick Bourgeat
β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3. NeuroImage 262: 119527 (2022) - [c63]Chao Li, Yue Cui, Na Luo
Trans-ResNet: Integrating Transformers and CNNs for Alzheimer's disease classification. ISBI 2022: 1-5 - [c62]Abdullah Thabit, Shenpeng Li, Rob Williams, Victor L. Villemagne, Christopher C. Rowe, Vincent Doré, Pierrick Bourgeat:
PET image harmonization using smoothing-CycleGAN. Medical Imaging: Computer-Aided Diagnosis 2022 - [c61]Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely. DALI@MICCAI 2022: 33-42 - [c60]Rodrigo Santa Cruz
CorticalFlow++: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability. MICCAI (5) 2022: 496-505 - [i5]Léo Lebrat, Rodrigo Santa Cruz, Frédéric de Gournay, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado
CorticalFlow: A Diffeomorphic Mesh Deformation Module for Cortical Surface Reconstruction. CoRR abs/2206.02374 (2022) - [i4]Rodrigo Santa Cruz, Léo Lebrat, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado
CorticalFlow++: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability. CoRR abs/2206.06598 (2022) - 2021
- [j21]Pierrick Bourgeat
Non-negative matrix factorisation improves Centiloid robustness in longitudinal studies. NeuroImage 226: 117593 (2021) - [j20]Biting Yu
SA-LuT-Nets: Learning Sample-Adaptive Intensity Lookup Tables for Brain Tumor Segmentation. IEEE Trans. Medical Imaging 40(5): 1417-1427 (2021) - [c59]Salamata Konate, Léo Lebrat
Smocam: Smooth Conditional Attention Mask For 3d-Regression Models. ISBI 2021: 362-366 - [c58]Rodrigo Santa Cruz
Going Deeper With Brain Morphometry Using Neural Networks. ISBI 2021: 711-715 - [c57]Filip Rusak, Rodrigo Santa Cruz, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley
Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation. SASHIMI@MICCAI 2021: 3-13 - [c56]Léo Lebrat, Rodrigo Santa Cruz, Frédéric de Gournay, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado:
CorticalFlow: A Diffeomorphic Mesh Transformer Network for Cortical Surface Reconstruction. NeurIPS 2021: 29491-29505 - [c55]Rodrigo Santa Cruz, Léo Lebrat
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction. WACV 2021: 806-815 - 2020
- [j19]Susmita Saha
Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model. NeuroImage 215: 116807 (2020) - [j18]Biting Yu
Sample-Adaptive GANs: Linking Global and Local Mappings for Cross-Modality MR Image Synthesis. IEEE Trans. Medical Imaging 39(7): 2339-2350 (2020) - [c54]Filip Rusak, Rodrigo Santa Cruz, Pierrick Bourgeat
3D Brain MRI GAN-Based Synthesis Conditioned on Partial Volume Maps. SASHIMI@MICCAI 2020: 11-20 - [c53]Biting Yu, Luping Zhou
Learning Sample-Adaptive Intensity Lookup Table for Brain Tumor Segmentation. MICCAI (4) 2020: 216-226 - [i3]Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat, Vincent Doré, Jason Dowling, Jurgen Fripp, Clinton Fookes, Olivier Salvado:
Going deeper with brain morphometry using neural networks. CoRR abs/2009.03303 (2020) - [i2]Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat, Clinton Fookes, Jurgen Fripp, Olivier Salvado:
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction. CoRR abs/2010.11423 (2020)
2010 – 2019
- 2019
- [j17]Biting Yu
Ea-GANs: Edge-Aware Generative Adversarial Networks for Cross-Modality MR Image Synthesis. IEEE Trans. Medical Imaging 38(7): 1750-1762 (2019) - [c52]Xingjuan Li
Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach. GLMI@MICCAI 2019: 96-103 - [i1]Malav Bateriwala, Pierrick Bourgeat:
Enforcing temporal consistency in Deep Learning segmentation of brain MR images. CoRR abs/1906.07160 (2019) - 2018
- [j16]Pierrick Bourgeat
Implementing the centiloid transformation for 11C-PiB and β-amyloid 18F-PET tracers using CapAIBL. NeuroImage 183: 387-393 (2018) - [c51]Biting Yu, Luping Zhou
3D cGAN based cross-modality MR image synthesis for brain tumor segmentation. ISBI 2018: 626-630 - [c50]Saba Momeni, Amir Fazlollahi, Pierrick Bourgeat
Data Augmentation Using Synthetic Lesions Improves Machine Learning Detection of Microbleeds from MRI. SASHIMI@MICCAI 2018: 12-19 - [c49]Amir Fazlollahi
A Framework to Objectively Identify Reference Regions for Normalizing Quantitative Imaging. MICCAI (1) 2018: 65-72 - 2017
- [c48]Amir Fazlollahi
A normalisation framework for quantitative brain imaging; application to quantitative susceptibility mapping. ISBI 2017: 97-100 - [c47]Pierrick Bourgeat
PET-only 18F-AV1451 tau quantification. ISBI 2017: 1173-1176 - 2016
- [j15]Jhimli Mitra, Kai-Kai Shen
Statistical machine learning to identify traumatic brain injury (TBI) from structural disconnections of white matter networks. NeuroImage 129: 247-259 (2016) - [c46]Anthony Paproki, Katharine J. Wilson, Rachel K. Surowiec, Charles P. Ho, Abinash Pant, Pierrick Bourgeat
Automated segmentation and T2-mapping of the posterior cruciate ligament from MRI of the knee: Data from the osteoarthritis initiative. ISBI 2016: 424-427 - [c45]Jhimli Mitra, Soumya Ghose, Pierrick Bourgeat
Anatomical hubs from spectral clustering of structural connectomes. ISBI 2016: 894-897 - [c44]Vincent Doré
CapAIBL: Automated Reporting of Cortical PET Quantification Without Need of MRI on Brain Surface Using a Patch-Based Method. Patch-MI@MICCAI 2016: 109-116 - 2015
- [j14]Amir Fazlollahi
Computer-aided detection of cerebral microbleeds in susceptibility-weighted imaging. Comput. Medical Imaging Graph. 46: 269-276 (2015) - [j13]Amir Fazlollahi
Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods. NeuroImage 117: 191-201 (2015) - [j12]David M. Cash
Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge. NeuroImage 123: 149-164 (2015) - [c43]Alex M. Pagnozzi
Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology. DICTA 2015: 1-6 - [c42]Abinash Pant, David Rivest-Hénault, Pierrick Bourgeat
Efficient Multi-scale Patch-Based Segmentation. Patch-MI@MICCAI 2015: 205-213 - [c41]Pierrick Bourgeat
Computational analysis of PET by AIBL (CapAIBL): a cloud-based processing pipeline for the quantification of PET images. Medical Imaging: Image Processing 2015: 94132V - 2014
- [j11]Christopher Bell, Kerstin Pannek
Distance informed Track-Weighted Imaging (diTWI): A framework for sensitising streamline information to neuropathology. NeuroImage 86: 60-66 (2014) - [j10]Jhimli Mitra, Pierrick Bourgeat
Lesion segmentation from multimodal MRI using random forest following ischemic stroke. NeuroImage 98: 324-335 (2014) - [j9]Yaniv Gal, Nicholas D. H. Dowson
Amorphous Regions-of-Interest Projection Method for Simplified Longitudinal Comparison of Dynamic Regions in Cancer Imaging. IEEE Trans. Biomed. Eng. 61(2): 264-272 (2014) - [c40]Amir Fazlollahi
Efficient machine learning framework for computer-aided detection of cerebral microbleeds using the Radon transform. ISBI 2014: 113-116 - 2013
- [j8]Pierrick Bourgeat
Research and applications: MilxXplore: a web-based system to explore large imaging datasets. J. Am. Medical Informatics Assoc. 20(6): 1046-1052 (2013) - [c39]Amir Fazlollahi
Automatic detection of small spherical lesions using multiscale approach in 3D medical images. ICIP 2013: 1158-1162 - [c38]Jhimli Mitra, Pierrick Bourgeat
Classification Forests and Markov Random Field to Segment Chronic Ischemic Infarcts from Multimodal MRI. MBIA 2013: 107-118 - 2012
- [j7]Ales Neubert
Constrained reverse diffusion for thick slice interpolation of 3D volumetric MRI images. Comput. Medical Imaging Graph. 36(2): 130-138 (2012) - [j6]Kai-Kai Shen
Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models. NeuroImage 59(3): 2155-2166 (2012) - [c37]Luping Zhou
MR-Less Surface-Based Amyloid Estimation by Subject-Specific Atlas Selection and Bayesian Fusion. MICCAI (2) 2012: 220-227 - [c36]Kai-Kai Shen
Consistent estimation of shape parameters in statistical shape model by symmetric EM algorithm. Medical Imaging: Image Processing 2012: 83140R - [c35]Vincent Doré
A surface based approach for cortical thickness comparison between PiB+ and PiB- healthy control subjects. Medical Imaging: Image Processing 2012: 831413 - 2011
- [c34]Vincent Doré
Surface-Base Approach Using a Multi-scale EM-ICP Registration for Statistical Population Analysis. DICTA 2011: 13-18 - [c33]Amir Fazlollahi
Automatic Brain Tumour Segmentation in 18F-FDOPA PET Using PET/MRI Fusion. DICTA 2011: 325-329 - [c32]Kai-Kai Shen
Atlas selection strategy using least angle regression in multi-atlas segmentation propagation. ISBI 2011: 1746-1749 - [c31]Parnesh Raniga
Local intensity model: An outlier detection framework with applications to white matter hyperintensity segmentation. ISBI 2011: 2057-2060 - [c30]Di Xiao, David Zahra, Pierrick Bourgeat
An accurate 3D shape context based non-rigid registration method for mouse whole-body skeleton registration. Medical Imaging: Image Processing 2011: 79620V - [c29]Kai-Kai Shen
Atlas selection strategy in multi-atlas segmentation propagation with locally weighted voting using diversity-based MMR re-ranking. Medical Imaging: Image Processing 2011: 79621B - [c28]Kai-Kai Shen
Detecting hippocampal shape changes in Alzheimer's disease using statistical shape models. Medical Imaging: Image Processing 2011: 796243 - 2010
- [j5]Di Xiao, David Zahra, Pierrick Bourgeat
An improved 3D shape context based non-rigid registration method and its application to small animal skeletons registration. Comput. Medical Imaging Graph. 34(4): 321-332 (2010) - [c27]Neil Burdett, Jurgen Fripp, Pierrick Bourgeat
MILXView: A Medical Imaging, Analysis and Visualization Platform. E-HEALTH 2010: 177-186 - [c26]Oscar Acosta
3D shape context surface registration for cortical mapping. ISBI 2010: 1021-1024 - [c25]Kai-Kai Shen
Supervised method to build an atlas database for multi-atlas segmentation-propagation. Medical Imaging: Computer-Aided Diagnosis 2010: 76241N - [c24]Kelvin K. Leung, Kai-Kai Shen
Increasing Power to Predict Mild Cognitive Impairment Conversion to Alzheimer's Disease Using Hippocampal Atrophy Rate and Statistical Shape Models. MICCAI (2) 2010: 125-132 - [c23]Nicholas D. H. Dowson
Joint Factor and Kinetic Analysis of Dynamic FDOPA PET Scans of Brain Cancer Patients. MICCAI (2) 2010: 185-192 - [c22]Di Xiao, David Zahra, Pierrick Bourgeat
An improved 3D shape context registration method for non-rigid surface registration. Medical Imaging: Image Processing 2010: 76232Q
2000 – 2009
- 2009
- [j4]Oscar Acosta
Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps. Medical Image Anal. 13(5): 730-743 (2009) - [c21]Andrea Rueda
Partial Volume Estimation of Brain Cortex from MRI Using Topology-Corrected Segmentation. ISBI 2009: 133-136 - [c20]Jurgen Fripp, Pierrick Bourgeat
Automated Segmentation of the Menisci from MR Images. ISBI 2009: 510-513 - [c19]Di Xiao, Pierrick Bourgeat
Non-rigid registration of small animal skeletons from micro-CT using 3D shape context. Medical Imaging: Image Processing 2009: 72591G - [c18]Jason Dowling
Nonrigid correction of interleaving artefacts in pelvic MRI. Medical Imaging: Image Processing 2009: 72592P - 2008
- [j3]Jurgen Fripp
Appearance modeling of 11C PiB PET images: Characterizing amyloid deposition in Alzheimer's disease, mild cognitive impairment and healthy aging. NeuroImage 43(3): 430-439 (2008) - [c17]Pierrick Bourgeat
Improved cortical thickness measurement from MR images using partial volume estimation. ISBI 2008: 205-208 - [c16]Jurgen Fripp, Pierrick Bourgeat
Generative atlases and atlas selection for C11-PIB PET-PET registration of elderly, mild cognitive impaired and Alzheimer disease patients. ISBI 2008: 1155-1158 - [c15]Oscar Acosta
Automatic Delineation of Sulci and Improved Partial Volume Classification for Accurate 3D Voxel-Based Cortical Thickness Estimation from MR. MICCAI (1) 2008: 253-261 - [c14]Jurgen Fripp, Pierrick Bourgeat
MR-Less High Dimensional Spatial Normalization of 11C PiB PET Images on a Population of Elderly, Mild Cognitive Impaired and Alzheimer Disease Patients. MICCAI (1) 2008: 442-449 - [c13]Maria A. Zuluaga
Cortical thickness measurement from magnetic resonance images using partial volume estimation. Medical Imaging: Image Processing 2008: 69140J - 2007
- [j2]Pierrick Bourgeat
MR image segmentation of the knee bone using phase information. Medical Image Anal. 11(4): 325-335 (2007) - [c12]Olivier Salvado
Fuzzy classificationof brain MRI using a priori knowledge: weighted fuzzy C-means. ICCV 2007: 1-8 - [c11]Parnesh Raniga
Pib-Pet Segmentation for Automatic Suvr Normalisation without Mr Information. ISBI 2007: 348-351 - [c10]Thanh-Mai Diep, Pierrick Bourgeat
Efficient Use of Cerebral Cortical Thickness to Correct Brain Mr Segmentation. ISBI 2007: 592-595 - [c9]Parnesh Raniga, Pierrick Bourgeat
Spline Based Inhomogeneity Correction for 11C-PIB PET Segmentation Using Expectation Maximization. MICCAI (1) 2007: 228-235 - [c8]Mark Holden, Rafael Moreno-Vallecillo, Anthony W. F. Harris
Expectation maximization classification and Laplacian based thickness measurement for cerebral cortex thickness estimation. Medical Imaging: Image Processing 2007: 65120M - [c7]Jurgen Fripp
Shape based segmentation of MRIs of the bones in the knee using phase and intensity information. Medical Imaging: Image Processing 2007: 651212 - 2006
- [c6]Pierrick Bourgeat
Texture-based segmentation of the knee bones in MRI using phase information. ISBI 2006: 742-745 - [c5]Pierrick Bourgeat
MR Image Segmentation Using Phase Information and a Novel Multiscale Scheme. MICCAI (2) 2006: 920-927 - 2005
- [c4]Jurgen Fripp, Pierrick Bourgeat
3D Statistical Shape Models to Embed Spatial Relationship Information. CVBIA 2005: 51-60 - [c3]Pierrick Bourgeat
Classifier vote and Gabor filter banks for wafer segmentation. ICIP (1) 2005: 369-372 - [c2]Pierrick Bourgeat
The Use of Unwrapped Phase in MR Image Segmentation: A Preliminary Study. MICCAI (2) 2005: 813-820 - 2004
- [j1]Pierrick Bourgeat
Content based segmentation of patterned wafers. J. Electronic Imaging 13(3): 428-435 (2004) - [c1]Pierrick Bourgeat
Features extraction on complex images. ICIP 2004: 219-222
Coauthor Index
Oscar Acosta
aka: Oscar Acosta Tamayo
aka: Oscar Acosta Tamayo
Jurgen Fripp
aka: Jurgen Mejan-Fripp
aka: Jurgen Mejan-Fripp
[j25] [c67] [c66] [c65] [c64] [j23] [j22] [c63] [c61] [c60] [i5] [i4] [j21] [j20] [c59] [c58] [c57] [c56] [c55] [j19] [j18] [c54] [c53] [i3] [i2] [j17] [c52] [j16] [c51] [c50] [c49] [c48] [c47] [j15] [c46] [c45] [c44] [j12] [c41] [j10] [j8] [c38] [j7] [j6] [c37] [c36] [c35] [c34] [c31] [c28] [c27] [c26] [c25] [c24] [j4] [c21] [c20] [c19] [c18] [j3] [c17] [c16] [c15] [c14] [j2] [c7] [c5] [c4] [c2]
Christopher Rowe
aka: Christopher C. Rowe
aka: Christopher C. Rowe
[c67] [c64] [c60] [i5] [i4] [c59] [c58] [c56] [c55] [c54] [i3] [i2] [j16] [c50] [c49] [c48] [c47] [j15] [c45] [c44] [j14] [j13] [j12] [c41] [j11] [j10] [j9] [c40] [j8] [c39] [c38] [j7] [j6] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [j5] [c27] [c26] [c25] [c24] [c22] [j4] [c21] [c20] [c19] [c18] [j3] [c17] [c16] [c15] [c14] [c13] [c12]
Victor Villemagne
aka: Victor L. Villemagne
aka: Victor L. Villemagne
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-05 21:14 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: