1. Chris McIntosh. Energy Functionals for Medical Image Segmentation: Choices and Consequences. Doctoral Thesis, School of Computing Science, Faculty of Applied Sciences, Simon Fraser University, November 2011. [bibtex-key = phd2011mcintosh]

1. Chris McIntosh and Ghassan Hamarneh. Medical Image Segmentation: Energy Minimization and Deformable Models (Chapter 23). Medical Imaging: Technology and Applications, pp 661-692, 2013. ISBN: 9781466582620. Keyword(s): Survey/Review, Segmentation, Deformable Models, Optimization. [bibtex-key = crc2013a]



2. Chris McIntosh and Ghassan Hamarneh. Medial-based Deformable Models in Non-convex Shape-spaces for Medical Image Segmentation using Genetic Algorithms. IEEE Transactions on Medical Imaging (IEEE TMI), 31(1):33-50, 2012. Keyword(s): Segmentation, Shape Modelling and Analysis, Deformable Models, Artificial Life, Optimization. [bibtex-key = tmi2012a]



3. Ghassan Hamarneh, Chris McIntosh, and Mark S. Drew. Perception-based Visualization of Manifold-Valued Medical Images using Distance-Preserving Dimensionality Reduction. IEEE Transactions on Medical Imaging (IEEE TMI), 30(7):1314-1327, 2011. Keyword(s): Color/Multichannel/Vector-valued, Visualization, Diffusion MRI/Tensor-valued, Functional/Molecular/Dynamic Imaging. [bibtex-key = tmi2011b]



4. Ghassan Hamarneh, Chris McIntosh, Tim McInerney, and Demetri Terzopoulos. Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis (Chapter 15). Computational Intelligence In Medical Imaging: Techniques and Applications, pp 433-474, 2009. ISBN: 978-1420060591. Keyword(s): Processing, Segmentation, Deformable Models, Deformable Organisms, Artificial Life, Bifurcation/Junction. [bibtex-key = crc2009]



5. Chris McIntosh and Ghassan Hamarneh. Evolutionary Deformable Models for Medical Image Segmentation: A Genetic Algorithm Approach to Optimizing Learned, Intuitive, and Localized Medial based Shape Deformation (Chapter 4.1). Genetic and Evolutionary Computation: Medical Applications, pp 47-67, 2009. ISBN: 978-0-470-74813-8. Keyword(s): Segmentation, Deformable Models, Artificial Life. [bibtex-key = gecma2009]



6. Ghassan Hamarneh and Chris McIntosh. Deformable Organisms for Medical Image Analysis (Chapter 12). Deformable Models: Biomedical and Clinical Applications, pp 387-443, 2007. ISBN: 978-0-387-31201-9. Keyword(s): Segmentation, Deformable Organisms, Artificial Life, Bifurcation/Junction. [bibtex-key = dm2007b]



7. Ghassan Hamarneh and Chris McIntosh. Physically and Statistically based Deformable Models for Medical Image Analysis (Chapter 11). Deformable Models: Biomedical and Clinical Applications, pp 335-386, 2007. ISBN: 978-0-387-31201-9. Keyword(s): Segmentation, Deformable Models. [bibtex-key = dm2007a]



8. Chris McIntosh and Ghassan Hamarneh. I-DO: A Deformable Organisms framework for ITK. Insight Journal, Special Issue: MICCAI 2006 Open Science Workshop:1-14, 2006. Keyword(s): Deformable Organisms, Software and Tools, Artificial Life. [bibtex-key = ij2006]

1. Jeremy Kawahara, Chris McIntosh, Roger Tam, and Ghassan Hamarneh. Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation. In Medical Image Computing and Computer-Assisted Intervention Workshop on Machine Learning in Medical Imaging (MICCAI MLMI), volume 8184, pages 212-219, 2013. Keyword(s): Segmentation, Machine Learning, Shape Modelling and Analysis, Multiple Sclerosis, MRI. [bibtex-key = miccai_mlmi2013a]



2. Jeremy Kawahara, Chris McIntosh, Roger Tam, and Ghassan Hamarneh. Globally Optimal Spinal Cord Segmentation using A Minimal Path in High Dimensions. In IEEE International Symposium on Biomedical Imaging (IEEE ISBI), pages 836-839, 2013. Keyword(s): Segmentation, Optimization, Anatomical Trees and Tubular Structures, Graph based, Multiple Sclerosis, MRI. [bibtex-key = isbi2013b]



3. Jeremy Kawahara, Chris McIntosh, Roger Tam, and Ghassan Hamarneh. Novel Morphological and Appearance Features for Predicting Physical Disability from MR Images in Multiple Sclerosis Patients. In Medical Image Computing and Computer-Assisted Intervention Workshop on Computational Methods and Clinical Applications for Spine Imaging (MICCAI CSI), pages 1-13, 2013. Keyword(s): Machine Learning, Shape Modelling and Analysis, Multiple Sclerosis, MRI. [bibtex-key = miccai_csi2013]



4. Shawn Andrews, Chris McIntosh, and Ghassan Hamarneh. Convex Multi-Region Probabilistic Segmentation with Shape Prior in the Isometric Logratio Transformation Space. In IEEE International Conference on Computer Vision (IEEE ICCV), pages 2096-2103, 2011. Keyword(s): Optimization, Segmentation, Uncertainty. [bibtex-key = iccv2011]



5. Chris McIntosh, Ghassan Hamarneh, Matt Toom, and Roger Tam. Spinal Cord Segmentation for Volume Estimation in Healthy and Multiple Sclerosis Subjects using Crawlers and Minimal Paths. In IEEE Conference on Healthcare Informatics, Imaging and Systems Biology (IEEE HISB), pages 25-31, 2011. Keyword(s): Artificial Life, Deformable Organisms, Segmentation, Anatomical Trees and Tubular Structures, Multiple Sclerosis, MRI. [bibtex-key = hisb2011b]



6. Chris McIntosh and Ghassan Hamarneh. Optimal Weights for Convex Functionals in Medical Image Segmentation. In International Symposium on Visual Computing: Special Track on Optimization for Vision, Graphics and Medical Imaging: Theory and Applications (ISVC OVGMI), volume 5875-I, pages 1079-1088, 2009. Keyword(s): Optimization, Segmentation, Machine Learning. [bibtex-key = isvc2009b]



7. Ghassan Hamarneh, Aaron Ward, Chris McIntosh, Ben Smith, Lisa Y. W. Tang, Ahmed Saad, Yonas Weldeselassie, and Omer Ishaq. Medical Image Analysis. In TechMed, Vancouver, May 16, 2007. Keyword(s): Segmentation, Shape Modelling and Analysis, Deformable Models, Deformable Organisms, Artificial Life, Imaging, Software and Tools. [bibtex-key = techmed2007]



8. Chris McIntosh and Ghassan Hamarneh. Is a Single Energy Functional Sufficient? Adaptive Energy Functionals and Automatic Initialization. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 4792, pages 503-510, 2007. Keyword(s): Deformable Models, Segmentation, Optimization, Machine Learning. [bibtex-key = miccai2007c]



9. Chris McIntosh, Ghassan Hamarneh, and Greg Mori. Human Limb Delineation and Joint Position Recovery Using Localized Boundary Models. In IEEE Workshop on Motion and Video Computing (IEEE WMVC), pages 31-38, 2007. Keyword(s): Segmentation, Deformable Models, Deformable Organisms, Tracking. [bibtex-key = wmvc2007]



10. Chris McIntosh and Ghassan Hamarneh. Genetic algorithm driven statistically deformed models for medical image segmentation. In ACM Workshop on Medical Applications of Genetic and Evolutionary Computation Workshop, in conjunction with the Genetic and Evolutionary Computation Conference (ACM GECCO MedGEC), pages 8 pages, 2006. Keyword(s): Segmentation, Shape Modelling and Analysis, Deformable Models, Artificial Life. [bibtex-key = medgec2006]



11. Chris McIntosh and Ghassan Hamarneh. I-DO: A Deformable Organisms framework for ITK. In Medical Image Computing and Computer-Assisted Intervention Open Science Workshop (also appears in the Insight Journal) (MICCAI OS), pages 1-14, 2006. Keyword(s): Deformable Organisms, Software and Tools, Artificial Life. [bibtex-key = miccai_os2006]



12. Chris McIntosh and Ghassan Hamarneh. Spinal Crawlers: Deformable Organisms for Spinal Cord Segmentation and Analysis. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), volume 4190, pages 808-815, 2006. Keyword(s): Segmentation, Deformable Models, Deformable Organisms, Artificial Life, Anatomical Trees and Tubular Structures. [bibtex-key = miccai2006]



13. Chris McIntosh and Ghassan Hamarneh. Vessel Crawlers: 3D Physically-based Deformable Organisms for Vasculature Segmentation and Analysis. In IEEE Conference on Computer Vision and Pattern Recognition (IEEE CVPR), pages 1084-1091, 2006. Keyword(s): Segmentation, Deformable Models, Deformable Organisms, Artificial Life, Anatomical Trees and Tubular Structures, Bifurcation/Junction. [bibtex-key = cvpr2006]



14. Ghassan Hamarneh and Chris McIntosh. Physics-based deformable organisms for medical image analysis. In SPIE Medical Imaging, volume 5747, pages 326-335, 2005. Keyword(s): Segmentation, Shape Modelling and Analysis, Medial-based Shape Representation, Deformable Organisms, Artificial Life. [bibtex-key = spiemi2005a]



15. Ghassan Hamarneh, Johnson Yang, Chris McIntosh, and Morgan Langille. 3D live-wire-based semi-automatic segmentation of medical images. In SPIE Medical Imaging, volume 5747, pages 1597-1603, 2005. Keyword(s): Segmentation, Deformable Models. [bibtex-key = spiemi2005c]



16. Chris McIntosh and Ghassan Hamarneh. Artificial Life Models for Medical Image Analysis - 2D and 3D ITK-Based Deformable Organisms. In 1st Annual Medical Technology Research Showcase, Vancouver, BC, 2005. Keyword(s): Segmentation, Deformable Organisms, Artificial Life, Bifurcation/Junction. [bibtex-key = medical_showcase2005c]



17. Ghassan Hamarneh and Chris McIntosh. Corpus Callosum Segmentation in Magnetic Resonance Images Using Artificial Organisms. In The MSHRF/CIHR Strategic Training Program in Neurobiology and Behaviour. Neuroscience Research Colloquia, Annual Neuroscience Extravaganza, Brain Research Centre, UBC, 11 2004. Keyword(s): Segmentation, Deformable Organisms, Artificial Life. [bibtex-key = neuroscix2004]

1. Shawn Andrews, Chris McIntosh, and Ghassan Hamarneh. Convex Multi-Region Probabilistic Segmentation with Shape Prior in the Isometric Logratio Transformation Space. Technical report TR 2011-03, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, July 2011. Keyword(s): Optimization, Segmentation, Uncertainty. [bibtex-key = sfu_cs2011_03]



2. Ghassan Hamarneh, Chris McIntosh, and Mark S. Drew. Perception-based Visualization of High-Dimensional Medical Images Using Distance Preserving Dimensionality Reduction. Technical report TR 2009-22, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, 11 2009. Keyword(s): Color/Multichannel/Vector-valued, Visualization, Diffusion MRI/Tensor-valued, Functional/Molecular/Dynamic Imaging. [bibtex-key = sfu_cs2009_22]



3. Chris McIntosh and Ghassan Hamarneh. Optimal Weights in Convex Functionals: Taking the Guesswork Out of Segmentation. Technical report TR 2009-14, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, 6 2009. Keyword(s): Optimization, Segmentation. [bibtex-key = sfu_cs2009_14]

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