Dr. Dzung L. Pham Profile

Dr. Dzung L. Pham

Director, CNRM Image Processing Core at Henry M Jackson Foundation

SPIE Involvement:

Conference Program Committee | Author

Area of Expertise:

medical image analysis , segmentation , neuroimaging

Websites:

Company Website

Profile Summary

Dzung L. Pham attended college at George Washington University, where he earned a BS degree in electrical engineering. He then received an MSE and PhD in electrical engineering from Johns Hopkins University. After his doctoral work, he accepted a research fellowship at the National Institute on Aging. He returned to Johns Hopkins as a Neuroradiology faculty member in 2002. In 2010, Dr. Pham became the director of the Image Processing Core within the Center for Neuroscience and Regenerative Medicine. His research interests include image processing and computer vision with application to biomedical imaging. He is particularly interested in the segmentation of medical images using stochastic and variational models.

Publications (24)

Proceedings Article | 15 March 2019

Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury

Samuel Remedios, Snehashis Roy, Justin Blaber, Camilo Bermudez, Vishwesh Nath, Mayur Patel, John Butman, Bennett Landman, Dzung Pham

Proc. SPIE. 10949, Medical Imaging 2019: Image Processing

KEYWORDS: Data modeling, Image segmentation, Neural networks, Machine learning, Computed tomography, Traumatic brain injury, Neuroimaging, Brain

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Proceedings Article | 15 March 2019

Cascaded convolutional neural networks for spine chordoma tumor segmentation from MRI

Syed M. Reza, Snehashis Roy, Deric Park, Dzung Pham, John Butman

Proc. SPIE. 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Convolutional neural networks, Tumors, Magnetic resonance imaging, Image segmentation, 3D modeling, Convolution, Skull, Spine, Brain

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Proceedings Article | 12 March 2018

Alternating segmentation and simulation for contrast adaptive tissue classification

Dzung Pham, Snehashis Roy

Proc. SPIE. 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Image processing algorithms and systems, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Medical imaging, Data acquisition, Neuroimaging, Brain

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Proceedings Article | 27 February 2018

Classifying magnetic resonance image modalities with convolutional neural networks

Samuel Remedios, Dzung Pham, John Butman, Snehashis Roy

Proc. SPIE. 10575, Medical Imaging 2018: Computer-Aided Diagnosis

KEYWORDS: Convolutional neural networks, Magnetic resonance imaging, Image processing, Image retrieval, Image classification, Neuroimaging, Brain

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Proceedings Article | 13 March 2017

Automatic falx cerebri and tentorium cerebelli segmentation from magnetic resonance images

Jeffrey Glaister, Aaron Carass, Dzung Pham, John Butman, Jerry Prince

Proc. SPIE. 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Image processing algorithms and systems, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Head, Finite element methods, Reconstruction algorithms, Neuroimaging, 3D visualizations, Cerebellum, Cerebrum, Brain

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Proceedings Article | 29 March 2016

Quantification of traumatic meningeal injury using dynamic contrast enhanced (DCE) fluid-attenuated inversion recovery (FLAIR) imaging

Marcelo Castro, Joshua Williford, Martin Cota, Judy MacLaren, Bernard Dardzinski, Lawrence Latour, Dzung Pham, John Butman

Proc. SPIE. 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Injuries, Curium, Magnetic resonance imaging, Image segmentation, Image registration, Head, Image enhancement, Traumatic brain injury, Neuroimaging, Brain

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Proceedings Article | 25 March 2016

Improved superficial brain hemorrhage visualization in susceptibility weighted images by constrained minimum intensity projection

Marcelo Castro, Dzung Pham, John Butman

Proc. SPIE. 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations

KEYWORDS: Skull

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Proceedings Article | 21 March 2016

Combining multi-atlas segmentation with brain surface estimation

Yuankai Huo, Aaron Carass, Susan Resnick, Dzung Pham, Jerry Prince, Bennett Landman

Proc. SPIE. 9784, Medical Imaging 2016: Image Processing

KEYWORDS: Image fusion, Magnetic resonance imaging, Image segmentation, Error analysis, Reconstruction algorithms, Cerebral cortex, Neuroimaging, Brain

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Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this “segmentation to surface to parcellation” strategy has shown limitation in various situations. In this work, we propose a novel “multi-atlas segmentation to surface” method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Proceedings Article | 21 March 2016

Segmentation and labeling of the ventricular system in normal pressure hydrocephalus using patch-based tissue classification and multi-atlas labeling

Lotta Ellingsen, Snehashis Roy, Aaron Carass, Ari Blitz, Dzung Pham, Jerry Prince

Proc. SPIE. 9784, Medical Imaging 2016: Image Processing

KEYWORDS: Tissues, Surgery, Magnetic resonance imaging, Image segmentation, Magnetism, Diagnostics, Image registration, Alzheimer's disease, Gait analysis, Classification systems, Dementia, Brain

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Proceedings Article | 20 March 2015

Cerebral microbleed segmentation from susceptibility weighted images

Snehashis Roy, Amod Jog, Elizabeth Magrath, John Butman, Dzung Pham

Proc. SPIE. 9413, Medical Imaging 2015: Image Processing

KEYWORDS: Image processing algorithms and systems, Image segmentation, Image processing, Transform theory, Traumatic brain injury, Spherical lenses, Strontium, Binary data, 3D image processing, Brain

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Proceedings Article | 20 March 2015

Intraparenchymal hemorrhage segmentation from clinical head CT of patients with traumatic brain injury

Snehashis Roy, Sean Wilkes, Ramon Diaz-Arrastia, John Butman, Dzung Pham

Proc. SPIE. 9413, Medical Imaging 2015: Image Processing

KEYWORDS: Tissues, Image segmentation, Neuroscience, Head, Computed tomography, Associative arrays, Regenerative medicine, Traumatic brain injury, Chemical elements, Brain

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Proceedings Article | 20 March 2015

Multi-output decision trees for lesion segmentation in multiple sclerosis

Amod Jog, Aaron Carass, Dzung Pham, Jerry Prince

Proc. SPIE. 9413, Medical Imaging 2015: Image Processing

KEYWORDS: Detection and tracking algorithms, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Feature extraction, Nervous system, Spinal cord, Neurons, Brain

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Proceedings Article | 18 March 2015

An example-based brain MRI simulation framework

Qing He, Snehashis Roy, Amod Jog, Dzung Pham

Proc. SPIE. 9412, Medical Imaging 2015: Physics of Medical Imaging

KEYWORDS: Data modeling, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Image acquisition, Physics, Computer simulations, Neuroimaging, Brain

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Proceedings Article | 21 March 2014

Example based lesion segmentation

Snehashis Roy, Qing He, Aaron Carass, Amod Jog, Jennifer Cuzzocreo, Daniel Reich, Jerry Prince, Dzung Pham

Proc. SPIE. 9034, Medical Imaging 2014: Image Processing

KEYWORDS: Ischemia, Tissues, Magnetic resonance imaging, Image segmentation, 3D modeling, Associative arrays, Alzheimer's disease, Neurological disorders, Model-based design, 3D image processing

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Proceedings Article | 13 March 2014

Characterizing the spatial distribution of microhemorrhages resulting from Traumatic Brain Injury (TBI)

Ningzhi Li, Yi-Yu Chou, Navid Shiee, Leighton Chan, Dzung Pham, John Butman

Proc. SPIE. 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Injuries, Visualization, Magnetic resonance imaging, Image segmentation, Image processing, Traumatic brain injury, Neuroimaging, 3D image processing, Diffusion tensor imaging, Brain

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Proceedings Article | 13 March 2013

Voxel-wise displacement as independent features in classification of multiple sclerosis

Min Chen, Aaron Carass, Daniel Reich, Peter Calabresi, Dzung Pham, Jerry Prince

Proc. SPIE. 8669, Medical Imaging 2013: Image Processing

KEYWORDS: Image fusion, Magnetic resonance imaging, Magnetism, Control systems, Image registration, Associative arrays, Scanning probe microscopy, Neuroimaging, Electroluminescent displays, Brain

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Proceedings Article | 16 April 2012

Quantitative evaluation of phase processing approaches in susceptibility weighted imaging

Ningzhi Li, Wen-Tung Wang, Pascal Sati, Dzung Pham, John Butman

Proc. SPIE. 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Tissues, Imaging systems, Image processing, Magnetism, Linear filtering, Gaussian filters, Image filtering, Homodyne detection, Image enhancement, Brain

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Proceedings Article | 13 March 2009

BrainIACS: a system for web-based medical image processing

Bhaskar Kishore, Pierre-Louis Bazin, Dzung Pham

Proc. SPIE. 7264, Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications

KEYWORDS: Image processing algorithms and systems, Human-machine interfaces, Phase modulation, Image processing, Interfaces, Computing systems, Medical imaging, Java, Algorithm development, Brain

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Proceedings Article | 29 April 2005

Free software tools for atlas-based volumetric neuroimage analysis

Pierre-Louis Bazin, Dzung Pham, William Gandler, Matthew McAuliffe

Proc. SPIE. 5747, Medical Imaging 2005: Image Processing

KEYWORDS: Tissues, Image segmentation, Image resolution, Image analysis, Medical imaging, Software development, Image classification, Neuroimaging, Cerebrum, Brain

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Proceedings Article | 29 April 2005

Super-resolved multi-channel fuzzy segmentation of MR brain images

Ying Bai, Xiao Han, Dzung Pham, Jerry Prince

Proc. SPIE. 5747, Medical Imaging 2005: Image Processing

KEYWORDS: Point spread functions, Super resolution, Magnetic resonance imaging, Image segmentation, Image processing, Image restoration, Image resolution, Neuroimaging, Fuzzy logic, Brain

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Proceedings Article | 15 May 2003

Automatic classification of sulcal regions of the human brain cortex using pattern recognition

Kirsten Behnke, Maryam Rettmann, Dzung Pham, Dinggang Shen, Susan Resnick, Christos Davatzikos, Jerry Prince

Proc. SPIE. 5032, Medical Imaging 2003: Image Processing

KEYWORDS: Magnetic resonance imaging, Image segmentation, Pattern recognition, Interfaces, Magnetism, Feature extraction, Image analysis, Image classification, Neuroimaging, Brain

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Proceedings Article | 9 May 2002

New approaches for measuring changes in the cortical surface using an automatic reconstruction algorithm

Dzung Pham, Xiao Han, Maryam Rettmann, Chenyang Xu, Duygu Tosun, Susan Resnick, Jerry Prince

Proc. SPIE. 4684, Medical Imaging 2002: Image Processing

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Interfaces, Image classification, Reconstruction algorithms, Cerebral cortex, Algorithm development, Natural surfaces, Brain

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Proceedings Article | 6 June 2000

Quantitative validation of a deformable cortical surface model

Daphne Yu, Chenyang Xu, Maryam Rettmann, Dzung Pham, Jerry Prince

Proc. SPIE. 3979, Medical Imaging 2000: Image Processing

KEYWORDS: Data modeling, Tissues, Magnetic resonance imaging, Image segmentation, Computer simulations, 3D modeling, Convolution, Neuroimaging, Natural surfaces, Brain

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Proceedings Article | 24 June 1998

Adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities

Dzung Pham, Jerry Prince

Proc. SPIE. 3338, Medical Imaging 1998: Image Processing

KEYWORDS: Image processing algorithms and systems, Image segmentation, Magnetism, Fuzzy logic

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Showing 5 of 24 publications

Conference Committee Involvement (7)

Image Processing

17 February 2020 | Houston, Texas, United States

Image Processing

19 February 2019 | San Diego, California, United States

Image Processing

11 February 2018 | Houston, Texas, United States

Image Processing

12 February 2017 | Orlando, Florida, United States

Image Processing Posters

12 February 2017 | Orlando, FL, United States

Showing 5 of 7 Conference Committees

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