Chris McIntosh
Chris McIntosh
Scientist, UHN; Assistant Professor, U of Toronto
Verified email at - Homepage
Cited by
Cited by
Transparency and reproducibility in artificial intelligence
B Haibe-Kains, GA Adam, A Hosny, F Khodakarami, ...
Nature 586 (7829), E14-E16, 2020
Vulnerabilities of radiomic signature development: the need for safeguards
ML Welch, C McIntosh, B Haibe-Kains, MF Milosevic, L Wee, A Dekker, ...
Radiotherapy and Oncology 130, 2-9, 2019
Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method
C McIntosh, M Welch, A McNiven, DA Jaffray, TG Purdie
Physics in Medicine & Biology 62 (15), 5926, 2017
Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer
C McIntosh, L Conroy, MC Tjong, T Craig, A Bayley, C Catton, ...
Nature medicine 27 (6), 999-1005, 2021
Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning
C McIntosh, TG Purdie
Physics in Medicine & Biology 62 (2), 415, 2016
3D live-wire-based semi-automatic segmentation of medical images
G Hamarneh, J Yang, C McIntosh, M Langille
Proceedings of SPIE Medical Imaging: Image Processing 5747, 1597-1603, 2005
Method and system for automated quality assurance and automated treatment planning in radiation therapy
TG Purdie, CJ McIntosh, I Svistoun
US Patent 10,475,537, 2019
Contextual atlas regression forests: multiple-atlas-based automated dose prediction in radiation therapy
C McIntosh, TG Purdie
IEEE transactions on medical imaging 35 (4), 1000-1012, 2015
Vessel crawlers: 3d physically-based deformable organisms for vasculature segmentation and analysis
C McIntosh, G Hamarneh
Computer Vision and Pattern Recognition, 2006 IEEE Computer Society …, 2006
Groupwise conditional random forests for automatic shape classification and contour quality assessment in radiotherapy planning
C McIntosh, I Svistoun, TG Purdie
IEEE transactions on medical imaging 32 (6), 1043-1057, 2013
Spinal crawlers: Deformable organisms for spinal cord segmentation and analysis
C McIntosh, G Hamarneh
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006, 808-815, 2006
Medial-based deformable models in nonconvex shape-spaces for medical image segmentation
C McIntosh, G Hamarneh
IEEE transactions on medical imaging 31 (1), 33-50, 2011
Convex Multi-Region Probabilistic Segmentation with Shape Prior in the Isometric Log-Ratio Transformation Space
S Andrews, C McIntosh, G Hamarneh
Is a single energy functional sufficient? Adaptive energy functionals and automatic initialization
C McIntosh, G Hamarneh
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2007, 503-510, 2007
Spinal Cord Segmentation for Volume Estimation in Healthy and Multiple Sclerosis Subjects using Crawlers and Minimal Paths
C McIntosh, G Hamarneh, M Toom, RC Tam
Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE …, 2011
Genetic algorithm driven statistically deformed models for medical image segmentation
C McIntosh, G Hamarneh
Genetic and Evolutionary Computation Conference, GECCO, 8-12, 2006
Perception-based Visualization of Manifold-Valued Medical Images using Distance-Preserving Dimensionality Reduction
G Hamarneh, C McIntosh, M Drew
Medical Imaging, IEEE Transactions on, 1-1, 2011
Globally optimal spinal cord segmentation using a minimal path in high dimensions
J Kawahara, C McIntosh, R Tam, G Hamarneh
2013 IEEE 10th International Symposium on Biomedical Imaging, 848-851, 2013
Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies
D Gustafson, M Ngai, R Wu, H Hou, AC Schoffel, C Erice, S Mandla, ...
EBioMedicine 78, 2022
Mass spectrometry imaging reveals a gradient of cancer-like metabolic states in the vicinity of cancer not seen in morphometric margins from microscopy
M Woolman, L Katz, G Gopinath, T Kiyota, CM Kuzan-Fischer, I Ferry, ...
Analytical chemistry 93 (10), 4408-4416, 2021
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