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Roger C. Tam
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- affiliation: University of British Columbia, BC, Canada
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2020 – today
- 2024
- [j15]Huilin Yang
, Junyan Lyu
LDDMM-Face: Large deformation diffeomorphic metric learning for cross-annotation face alignment. Pattern Recognit. 154: 110569 (2024) - [j14]Yijin Huang
SSiT: Saliency-Guided Self-Supervised Image Transformer for Diabetic Retinopathy Grading. IEEE J. Biomed. Health Informatics 28(5): 2806-2817 (2024) - [c31]Yijin Huang, Pujin Cheng, Roger C. Tam, Xiaoying Tang:
Fine-Grained Prompt Tuning: A Parameter and Memory Efficient Transfer Learning Method for High-Resolution Medical Image Classification. MICCAI (12) 2024: 120-130 - [i5]Yijin Huang, Pujin Cheng, Roger C. Tam, Xiaoying Tang:
FPT: Fine-grained Prompt Tuning for Parameter and Memory Efficient Fine Tuning in High-resolution Medical Image Classification. CoRR abs/2403.07576 (2024) - [i4]Yijin Huang, Pujin Cheng, Roger C. Tam, Xiaoying Tang:
FPT+: A Parameter and Memory Efficient Transfer Learning Method for High-resolution Medical Image Classification. CoRR abs/2408.02426 (2024) - 2023
- [c30]Huilin Yang, Roger C. Tam, Xiaoying Tang:
Whole-Heart Reconstruction with Explicit Topology Integrated Learning. MICCAI (6) 2023: 106-115 - [c29]Yuanyuan Wei, Roger C. Tam, Xiaoying Tang:
MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging. MIDL 2023: 1798-1812 - [i3]Yuanyuan Wei
MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging. CoRR abs/2304.06258 (2023) - 2022
- [i2]Yijin Huang, Junyan Lyu
SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy Grading. CoRR abs/2210.10969 (2022) - 2021
- [j13]Bruno César Gregório da Silva
Detecting cells in intravital video microscopy using a deep convolutional neural network. Comput. Biol. Medicine 129: 104133 (2021) - [j12]Katia Maria Poloni
Brain MR image classification for Alzheimer's disease diagnosis using structural hippocampal asymmetrical attributes from directional 3-D log-Gabor filter responses. Neurocomputing 419: 126-135 (2021) - [j11]Rachel A. Crockett
Painting by lesions: White matter hyperintensities disrupt functional networks and global cognition. NeuroImage 236: 118089 (2021) - 2020
- [j10]Hanwen Liu
Myelin water imaging data analysis in less than one minute. NeuroImage 210: 116551 (2020) - [c28]Shahab Aslani, Vittorio Murino, Michael Dayan
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI. ISBI 2020: 781-785 - [c27]Lisa Y. W. Tang
Predicting Catheter Ablation Outcomes with Pre-ablation Heart Rhythm Data: Less Is More. MLMI@MICCAI 2020: 563-571
2010 – 2019
- 2019
- [j9]Youngjin Yoo, Lisa Y. W. Tang, David K. B. Li, Luanne Metz, Shannon H. Kolind, Anthony Traboulsee, Roger C. Tam
Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 7(3): 250-259 (2019) - [i1]Shahab Aslani, Vittorio Murino, Michael Dayan, Roger C. Tam, Diego Sona, Ghassan Hamarneh:
Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI. CoRR abs/1910.10035 (2019) - 2017
- [j8]Ferran Prados
Spinal cord grey matter segmentation challenge. NeuroImage 152: 312-329 (2017) - [c26]Adam Porisky, Tom Brosch, Emil Ljungberg
Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections. DLMIA/ML-CDS@MICCAI 2017: 330-337 - [c25]Youngjin Yoo, Lisa Y. W. Tang, Su-Hyun Kim, Ho Jin Kim, Lisa Eunyoung Lee
Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis. MICCAI (3) 2017: 480-488 - 2016
- [j7]Tom Brosch, Lisa Y. W. Tang
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation. IEEE Trans. Medical Imaging 35(5): 1229-1239 (2016) - [c24]Lisa Y. W. Tang, Roger C. Tam
Enhancing accuracy of symmetric random walker image registration via a novel data-consistency measure. ISBI 2016: 28-31 - [c23]Youngjin Yoo, Lisa Y. W. Tang, Tom Brosch, David K. B. Li, Luanne Metz, Anthony Traboulsee, Roger C. Tam
Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis. LABELS/DLMIA@MICCAI 2016: 86-94 - [c22]Lisa Y. W. Tang
Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction. MICCAI (2) 2016: 406-414 - 2015
- [j6]Tom Brosch, Roger C. Tam
Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images. Neural Comput. 27(1): 211-227 (2015) - [c21]Saurabh Garg, Lisa Tang, Anthony Traboulsee, Roger C. Tam
A sensitive and efficient method for measuring change in cortical thickness using fuzzy correspondence in Alzheimer's disease. ICIP 2015: 3014-3018 - [c20]Tom Brosch, Youngjin Yoo, Lisa Y. W. Tang, David K. B. Li, Anthony Traboulsee, Roger C. Tam
Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation. MICCAI (3) 2015: 3-11 - [c19]Lisa Y. W. Tang, Ghassan Hamarneh
Corpus Callosum Segmentation in MS Studies Using Normal Atlases and Optimal Hybridization of Extrinsic and Intrinsic Image Cues. MICCAI (3) 2015: 123-131 - 2014
- [c18]Youngjin Yoo, Tom Brosch, Anthony Traboulsee, David K. B. Li, Roger C. Tam
Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation. MLMI 2014: 117-124 - [c17]Tom Brosch, Youngjin Yoo, David K. B. Li, Anthony Traboulsee
Modeling the Variability in Brain Morphology and Lesion Distribution in Multiple Sclerosis by Deep Learning. MICCAI (2) 2014: 462-469 - 2013
- [c16]Jeremy Kawahara, Chris McIntosh
Globally optimal spinal cord segmentation using a minimal path in high dimensions. ISBI 2013: 848-851 - [c15]Jeremy Kawahara, Chris McIntosh
Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation. MLMI 2013: 211-218 - [c14]Youngjin Yoo, Roger C. Tam
Non-Local Spatial Regularization of MRI T2 Relaxation Images for Myelin Water Quantification. MICCAI (1) 2013: 614-621 - [c13]Tom Brosch, Roger C. Tam
Manifold Learning of Brain MRIs by Deep Learning. MICCAI (2) 2013: 633-640 - 2012
- [c12]Fahime Sheikhzadeh, Roger C. Tam
Spatial dispersion of lesions as a surrogate biomarker for disability in multiple sclerosis. MMBIA 2012: 273-278 - 2011
- [c11]Chris McIntosh
Spinal Cord Segmentation for Volume Estimation in Healthy and Multiple Sclerosis Subjects Using Crawlers and Minimal Paths. HISB 2011: 25-31 - 2010
- [j5]Jon McAusland, Roger C. Tam
Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation. IEEE Trans. Biomed. Eng. 57(11): 2689-2698 (2010) - [j4]Albert Huang, Rafeef Abugharbieh, Roger C. Tam
A Novel Rotationally Invariant Region-Based Hidden Markov Model for Efficient 3-D Image Segmentation. IEEE Trans. Image Process. 19(10): 2737-2748 (2010) - [c10]Neda Changizi, Ghassan Hamarneh
Extraction of the Plane of Minimal Cross-Sectional Area of the Corpus Callosum Using Template-Driven Segmentation. MICCAI (3) 2010: 17-24
2000 – 2009
- 2009
- [j3]Roger C. Tam
Detection and measurement of coverage loss in interleaved multi-acquisition brain MRIs due to motion-induced inter-slice misalignment. Medical Image Anal. 13(3): 381-391 (2009) - [j2]Albert Huang, Rafeef Abugharbieh, Roger C. Tam
A Hybrid Geometric-Statistical Deformable Model for Automated 3-D Segmentation in Brain MRI. IEEE Trans. Biomed. Eng. 56(7): 1838-1848 (2009) - [c9]Albert Huang, Rafeef Abugharbieh, Roger C. Tam
A Fuzzy Region-Based Hidden Markov Model for Partial-Volume Classification in Brain MRI. MICCAI (1) 2009: 474-481 - 2008
- [c8]Albert Huang, Rafeef Abugharbieh, Roger C. Tam:
Image segmentation using an efficient rotationally invariant 3D region-based hidden Markov model. CVPR Workshops 2008: 1-8 - 2006
- [c7]Albert Huang, Rafeef Abugharbieh, Roger C. Tam, Anthony Traboulsee:
Automatic MRI brain tissue segmentation using a hybrid statistical and geometric model. ISBI 2006: 394-397 - [c6]Albert Huang, Rafeef Abugharbieh, Roger C. Tam
Brain extraction using geodesic active contours. Medical Imaging: Image Processing 2006: 61444J - 2004
- [c5]Roger C. Tam
Computing Polygonal Surfaces from Unions of Balls. Computer Graphics International 2004: 86-92 - 2003
- [c4]Roger C. Tam
Shape Simplification Based on the Medial Axis Transform. IEEE Visualization 2003: 481-488 - 2002
- [c3]Roger C. Tam
Feature-Preserving Medial Axis Noise Removal. ECCV (2) 2002: 672-686 - 2001
- [c2]Roger C. Tam, Alain Fournier:
Shape Model and Threshold Extraction via Shape Gradients. VMV 2001: 481-490
1990 – 1999
- 1998
- [j1]Roger C. Tam
Image interpolation using unions of spheres. Vis. Comput. 14(8/9): 401-414 (1998) - 1997
- [c1]Roger C. Tam, Christopher G. Healey, Borys Flak, Peter Cahoon:
Volume rendering of abdominal aortic aneurysms. IEEE Visualization 1997: 43-50
Coauthor Index
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