Adrian Vasile Dalca

CV | scholar | linkedin | twitter | github

Assistant Professor, A.A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital, Harvard Medical School

Research Scientist, Computer Science and Artificial Intelligence Lab
EECS, Massachusetts Institute of Technology

Contact:
32 Vassar St, 32-G904, Cambridge, MA, 02139 
adalca at mit dot edu

Publications

See my google scholar profile

On this page: preprints · peer reviewed papers · peer revieweed workshops · theses · books and proceedings

Preprints

• preprint
  Learning image registration without images.
  M. Hoffmann, B. Billot, J.E. Iglesias, B. Fischl, A.V. Dalca
  [ arXiv preprint ]
• preprint
  Joint Frequency- and Image-Space Learning for Fourier Imaging.
  N.M. Singh, J.E. Iglesias, E. Adalsteinsson, A.V. Dalca, P. Golland
  [ arXiv preprint ]
• preprint
  Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks.
  A.Q. Wang, A.V. Dalca, M. R. Sabuncu
  [ arXiv preprint ]

Peer Reviewed Publications

• conference
  HyperMorph: Amortized Hyperparameter Learning for Image Registration.
  A. Hoopes, M. Hoffmann, B. Fischl, J. Guttag, A.V. Dalca
  IPMI: Information Processing and Medical Imaging. In Press. 2021.
  [ arXiv preprint | Oral Presentation ]
• conference
  Learning MRI contrast-agnostic registration.
  M. Hoffmann, B. Billot, J.E. Iglesias, B. Fischl, A.V. Dalca
  ISBI: International Symposium on Biomedical Imaging. In Press. 2021
  [ Oral Presentation ]
• conference
  Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction.
  A. Raghu, J. Guttag, K. Young, E. Pomerantsev, A.V. Dalca, C. Stultz
  ACM CHIL: Conference on Healthcare, Inference, and Learning. In Press. 2021.
• conference
  Joint segmentation of Multiple Sclerosis lesions and brain anatomy in MRI scans of any contrast and resolution with CNNs.
  B. Billot, S. Cerri, K. v. Leemput, A. V. Dalca J. E. Iglesias
  ISBI: International Symposium on Biomedical Imaging. In Press. 2021.
  [ Oral Presentation ]
• conference
  A Learning Strategy for Contrast-agnostic MRI Segmentation.
  B. Billot, D. Greve, K. Van Leemput, B. Fischl, J. E. Iglesias^‡, A. V. Dalca^‡
  MIDL: Medical Imaging with Deep Learning. PMLR 121. pp 75-93. 2020.
  [ arXiv preprint | Oral Presentation | Open Review ]
• conference
  Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings
  A. Zhao, G. Balakrishnan, K. M. Lewis, F. Durand, J. Guttag, A.V. Dalca.
  CVPR: Computer Vision and Pattern Recognition. pp. 8435-8445. 2020.
  [ arXiv preprint | video | website | engaget ]
• conference
  Fast Learning-based Registration of Sparse 3D Clinical Images
  K. Lewis, N, Rost, J. Guttag, A.V. Dalca
  ACM CHIL: Conference on Healthcare, Inference, and Learning. pp 90-98. 2020.
  [ arXiv preprint ]
• journal
  Cortical surface registration using unsupervised learning.
  J. Cheng, A.V. Dalca, B. Fischl^‡, L. Zollei^‡.
  Neuroimage. 221. pp. 117161-117173. 2020.
  [ arXiv preprint ]
• journal
  Deep-learning-based Optimization of the Under-sampling Pattern in MRI
  C. Bahadir^‡, A.Q. Wang^‡, A.V. Dalca, M.R. Sabuncu.
  IEEE TCP: Transactions on Computational Imaging. 6. pp. 1139-1152. 2020.
  [ arXiv preprint ]
• conference
  Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast.
  B. Billot, E.D. Robinson, A.V. Dalca, J.E. Iglesias
  MICCAI: Medical Image Computing and Computer Assisted Intervention. LNCS 12267. pp 177-187. 2020.
  [ arXiv preprint | Early Accept ]
• conference
  Learning a Probabilistic Strategy for Computational Imaging Sensor Selection
  H. Sun, A.V. Dalca, K. Bouman
  IEEE ICCP: International Conference on Computational Photography. pp. 1-12. 2020.
  [ arXiv preprint | code ]
• conference
  An Auto-Encoder Strategy for Adaptive Image Segmentation.
  E. M. Yu, J. E. Iglesias, A. V. Dalca, M. R. Sabuncu
  MIDL: Medical Imaging with Deep Learning. PMLR 121. pp 881-891. 2020.
  [ Spotlight | arXiv preprint | Open Review ]
•   journal
  White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype
  A.K. Giese, M.D. Schirmer, A.V. Dalca, R. Sridharan, K. Donahue, M. Nardin, R. Irie, et al (34 authors)
  Neurology. 95 (1). pp e79-e88. 2020.
  [ Paper link ]
•   conference
  3D reconstruction and segmentation of dissection photographs for MRI-free neuropathology
  H Tregidgo, A Casamitjana, C Latimer, M Kilgore, N Robinson, E Blackburn, K Van Leemput, B Fischl, A.V. Dalca, C MacDonald, D Keene, JE Iglesias
  MICCAI: Medical Image Computing and Computer Assisted Intervention. LNCS 12265. pp. 204-214. 2020.
  
• journal
  Automated segmentation of the Hypothalamus and associated subunits in brain MRI.
  B. Billot, M. Bocchetta, E. Todd, A. V. Dalca, J.D. Rohrer, J. E. Iglesias
  NeuroImage. 223. pp 117287-117299. 2020.
  
• journal
  Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation
  F. Dubost, M. de Bruijne, M. Nardin, A. V. Dalca, K.L. Donahue, A-K Giese, et al (13 authors)
  MedIA: Medical Image Analysis. 63. pp 101698. 2020.
  [ arXiv preprint ]
•   journal
  Diffusion Weighted Imaging, MR Angiography and Baseline Data in a Systematic Multi-Center Analysis of 3301 MRI Scans of Ischemic Stroke Patients - Neuroradiological review within the MRI-GENIE study
  M. Drake et al (41 authors)
  Frontiers in Neurology. 11. pp 577. 2020.
  [ paper ]
•   journal
  Detailed phenotyping of posterior vs. Anterior circulation ischemic stroke: a multi-center MRI study
  P. Frid et al (44 authors)
  Journal of Neurology. 267(3) pp 649-658. 2020.
  
•   journal
  Brain volume: An important determinant of functional outcome after acute ischemic stroke
  M.D. Schirmer, K.L. Donahue, M.J. Nardin, A.V. Dalca, A.K. Giese, M.R. Etherton, et al (41 authors)
  Mayo Clinic Proceedings. 95(5). pp 955-965. 2020.
  
• conference
  Learning Conditional Deformable Templates with Convolutional Networks
  A.V. Dalca, M. Rakic, J. Guttag, M.R. Sabuncu.
  NeurIPS: Advances in Neural Information Processing Systems. pp 804-816, 2019.
  [ arXiv preprint ]
• journal
  Unsupervised Learning for Probabilistic Diffeomorphic Registration for Images and Surfaces
  A.V. Dalca, G. Balakrishnan, J. Guttag, M.R. Sabuncu.
  MedIA: Medical Image Analysis. (57). pp 226-236, 2019
  [ arXiv preprint ]
• conference
  Unsupervised deep learning for Bayesian brain MRI segmentation
  A.V. Dalca, E Yu, P Golland, B Fischl, M R. Sabuncu, J E. Iglesias
  MICCAI: Medical Image Computing and Computer Assisted Intervention. LNCS 11766. pp 356-365. 2019.
  [ arXiv preprint ]
• conference
  Data Augmentation with Spatial and Appearance Transforms for One-shot Medical Image Segmentation
  A. Zhao, G. Balakrishnan, F. Durand, J. Guttag, A.V. Dalca.
  CVPR: Computer Vision and Pattern Recognition. pp 8543-8553. 2019.
  [ Oral Presentation - video | paper | MIT News ]
• journal
  VoxelMorph: A Learning Framework for Deformable Medical Image Registration
  G. Balakrishnan, A. Zhao, M. R. Sabuncu, J. Guttag, A.V. Dalca.
  IEEE TMI: Transactions on Medical Imaging. 38(8). pp 1788-1800. 2019.
  [ paper ]
• conference
  Learning-based Optimization of the Under-sampling Pattern in MRI
  C. Bahadir A.V. Dalca, M.R. Sabuncu.
  IPMI: Information Processing and Medical Imaging. LNCS 11492. pp 780-792. 2019.
  [ arXiv preprint ]
•   journal
  Medical Image Imputation from Image Collections
  A.V. Dalca, K.L. Bouman, W.T. Freeman, N.S. Rost, M.R. Sabuncu, P. Golland.
  IEEE TMI: Transactions on Medical Imaging, 38 (2), pp 504-514. 2019.
  [ paper ]
• conference
  Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions in Images and Videos
  G. Balakrishnan, A.V. Dalca, A. Zhao, J. Guttag, F. Durand, W. T. Freeman.
  ICCV: International Conference in Computer Vision. pp 171-180. 2019.
  [ arXiv preprint ]
•   journal
  White Matter Hyperintensity Quantification in Large-Scale Clinical Acute Ischemic Stroke Cohorts
  M.D. Schirmer, A.V. Dalca, R. Sridharan, A.K. Giese, K.L. Donahue, M.J. Nardin, et al (34 authors)
  Neuroimage: Clinical. 23. pp 101884-101896. 2019.
  [ biorxiv preprint ]
•   journal
  Trends and Focus of Machine Learning Applications for Health Research
  B. Beaulieu-Jones, S. G. Finlayson, C. Chivers, I. Chen, M. McDermott, J. Kandola, A.V. Dalca, A. Beam, M. Fiterau, T. Naumann
  JAMA network open. 2 (10). 2019.
  [ paper ]
• conference
  Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration
  A.V. Dalca, G. Balakrishnan, J. Guttag, M.R. Sabuncu.
  MICCAI: Medical Image Computing and Computer Assisted Intervention. LNCS 11070, pp 729-738. 2018.
  [ paper | code | news article ]
  [ Finalist: Best paper (young scientist) award | Early accept | Oral Presentation | Best Poster at MLIM ]
• conference
  Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation.
  A.V. Dalca, J. Guttag, M. R. Sabuncu.
  CVPR: Computer Vision and Pattern Recognition. pp 9290-9299. 2018.
  [ paper | code ]
• conference
  An Unsupervised Learning Model for Deformable Medical Image Registration.
  G. Balakrishnan, A. Zhao, M. R. Sabuncu, J. Guttag, A.V. Dalca.
  CVPR: Computer Vision and Pattern Recognition. pp 9252-9260. 2018.
  [ paper | code | news articles: MIT News, Engaget, Forbes, ExtremeTech ]
• conference
  Gaussian Process Prior Variational Autoencoders.
  F.P. Casale, A. V. Dalca, L. Saglietti, N. Fusi, J. Listgarten.
  NeurIPS: Advances in Neural Information Processing Systems. pp 10369-10380. 2018.
  [ paper | supp. materials ]
• conference
  Synthesizing Images of Humans in Unseen Poses.
  G. Balakrishnan, A. Zhao, A.V. Dalca, F. Durand, J. Guttag.
  CVPR: Computer Vision and Pattern Recognition. pp 8340-8348. 2018.
  [ paper | code | news article | Oral Presentation ]
•   journal
  Reconstructing Video of Time-Varying Sources from Radio Interferometric Measurements
  K.L. Bouman, M.D. Johnson, A.V. Dalca, A.A. Chael, F.Roelofs, S.S. Doeleman, W.T. Freeman.
  IEEE TCI: Transactions on Computational Imaging. 4.4. pp. 512-527. 2018.
  [ arXiv preprint | IEEE Early Access ]
• conference
  Population Based Image Imputation.
  A.V. Dalca, K.L. Bouman, W.T. Freeman, M.R. Sabuncu, N.S. Rost, P. Golland.
  IPMI: Information Processing and Medical Imaging. LNCS 10265, pp 659-671. 2017.
  [ paper | News article | Best poster award ]
• conference
  Frequency Diffeomorphisms for Efficient Image Registration.
  M. Zhang, R. Liao, A.V. Dalca, E.A. Turk, J. Luo, E. Grant, P. Golland.
  IPMI: Information Processing and Medical Imaging. LNCS 10265, pp 559-570. 2017.
  [ paper | Oral Presentation ]
•   journal
  Design and Rationale for Examining Neuroimaging Genetics in Ischemic Stroke: the MRI-GENIE Study.
  A.K. Giese, M.D. Schirmer, K.L. Donahue, L. Cloonan, R. Irie, S. Winzeck, M.J. Bouts, E.C. McIntosh, S. J. Mocking, A.V. Dalca, et al.
  Neurology: Genetics. 3(5). 2017.
  [ PMC paper ]
•   journal
  Probabilistic Modeling of Imaging, Genetics and Diagnosis.
  K.N. Batmanghelich, A.V. Dalca, G. Quon, M.R. Sabuncu, P. Golland.
  IEEE TMI: Transactions on Medical Imaging, 35(7), pp 1765-79, 2016.
  [ paper ]
• conference
  Predictive Modeling of Anatomy with Genetic and Clinical Data.
  A.V. Dalca, R. Sridharan, M.R. Sabuncu, P. Golland.
  MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS 9351, pp. 519-526, 2015.
  [ paper | Poster | Video | news article ]
• conference
  Interactive Whole-Heart Segmentation in Congenital Heart Disease.
  D. Pace, A.V. Dalca, T.Geva, A.J. Powell, M.H. Moghari, P. Golland.
  MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS 9351, pp. 80-88, 2015.
  [ paper | news article ]
• conference
  Segmentation of Cerebrovascular Pathologies in Stroke Patients with Spatial and Shape Priors.
  A.V. Dalca, R. Sridharan, L. Cloonan, K. M. Fitzpatrick, A. Kanakis, K.L. Furie, J.Rosand, O.Wu, M.Sabuncu, N.S. Rost, P.Golland.
  MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS 8674, pp. 773-780, 2014.
  [ paper | Poster PDF | doi ]
• conference
  Joint Modeling of Imaging and Genetics.
  K.N. Batmanghelich, A.V. Dalca, M.R. Sabuncu, P. Golland.
  IPMI: Information Processing and Medical Imaging, LNCS 7917, pp. 766-777, 2013.
  [ paper | Oral Presentation | doi ]
•   journal
  On Post-glacial Sea-Level - III: Incorporating Sediment Redistribution.
  A.V. Dalca, K.L.Ferrier, J.X.Mitrovica, J.T. Perron, G.A. Milne, J.R. Creveling.
  Geophysical Journal International, 2013.
  [ paper | doi ]
• conference
  Segmentation of Nerve Bundles and Ganglia in Spine MRI using Particle Filters.
  A.V. Dalca, G. Danagoulian, R. Kikinis, E. Schmidt, P. Golland.
  MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS, vol. 6893, pp 537-545, 2011.
  [ paper | doi | Pubmed | Poster PDF ]
•   journal
  VARiD: A variation detection framework for color-space and letter-space platforms.
  A.V. Dalca, S.M. Rumble, S. Levy and M. Brudno.
  Bioinformatics,26: i343-i349, 2010.
  [ paper | doi | Website | Pubmed | together with ISMB 2010: Oral Presentation ]
•   journal
  Genome Variation Discovery with High Throughput Sequencing Data.
  A.V. Dalca and M. Brudno.
  Briefings in Bioinformatics, 11. p3-14, 2010.
  [ paper | doi | Pubmed ]
•   journal
  SHRiMP Accurate Mapping of Short Color-space Reads.
  S.M. Rumble, P. Lacroute, A.V. Dalca, M. Fiume, A. Sidow, M. Brudno.
  PLoS Computational Biology, 5(5), 2009.
  [ paper |  Website | doi | Pubmed ]
• conference
  FRESCO: Flexible Alignment with Rectangle Scoring Schemes.
  A.V. Dalca and M. Brudno.
  Pacific Symposium on Biocomputing, 13. p3-14, 2008.
  [ paper | Website | Pubmed | Oral Presentation ]

Peer Reviewed Workshop / short Publications

• conference
  Anatomical Predictions using Subject-Specific Medical Data.
  M. Rakic, J. Guttag, A.V. Dalca.
  MIDL: Medical Imaging with Deep Learning. Short Paper. 2020.
  [ Open Review ]
• workshop
  Learning MRI contrast agnostic registration.
  M. Hoffmann, B. Billot, J.E. Iglesias, B. Fischl, A.V. Dalca
  MED NeurIPS: Medical Imaging Meets NeurIPS. Extended Abstract. 2020.
  [ arXiv preprint | interactive video ]
• workshop
  Neural Network-based Reconstruction in Compressed Sensing MRI Without Fully-sampled Training Data.
  A.Q. Wang, A.V. Dalca, M.R.Sabuncu.
  MICCAI MLMIR: Machine Learning for Medical Image Reconstruction. In Press. Springer. 2020.
  [ arXiv preprint ]
• workshop
  Learning Conditional Deformable Shape Templates for Brain Anatomy.
  E. Yu, A.V. Dalca, M.R.Sabuncu.
  MICCAI MLMI: Machine Learning in Medical Imaging. In Press. Springer. 2020.
• workshop
  Unbiased atlas construction for neonatal cortical surfaces via unsupervised learning.
  J. Cheng, A.V. Dalca, L. Zollei.
  MICCAI PIPPI: Perinatal, Preterm and Paediatric Image Analysis. In Press. Springer. 2020.
• workshop
  Learning to Predict and Support for Clinical Risk Stratification
  A. Raghu, K. Young, E. Pomerantsev, J. Guttag, A. V. Dalca C. Stultz
  NeurIPS ML4H: Machine Learning for Health. Extended Abstract. 2020.
• workshop
  Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
  H. W. Lee, M. R. Sabuncu, A. V. Dalca
  NeurIPS ML4H: Machine Learning for Health. 2019.
  [ arXiv preprint ]
• workshop
  Unsupervised Medical Image Imputation via Variational Inference of Deep Subspaces
  A.V. Dalca, J. Guttag, M. R. Sabuncu.
  NeurIPS ML4H: Machine Learning for Health. 2018.
  [ arXiv preprint ]
• workshop
  Atlas Construction and Improved Registration of Medical Images with CNN Frameworks
  A.V. Dalca, G. Balakrishnan, J. Guttag, M. R. Sabuncu.
  NeurIPS ML4H: Machine Learning for Health. 2018.
  
• workshop
  Improved Probabilistic Diffeomorphic Registration with CNNs
  A.V. Dalca, G. Balakrishnan, J. Guttag, M. R. Sabuncu.
  MED NeurIPS: Medical Imaging Meets NeurIPS. 2018.
  [ paper | Oral Presentation ]
• workshop
  Fast Learning-based Registration of Sparse Clinical Images
  K. Lewis, G. Balakrishnan, N, Rost, J. Guttag and A.V. Dalca
  NeurIPS ML4H: Machine Learning for Health. 2018.
  [ paper | Spotlight ]
• workshop
  Generative Models for Clinical Imaging Genetic Analysis
  F. P. Casale, A.V. Dalca, N. Fusi and J. Listgarten
  NeurIPS ML4H: Machine Learning for Health. 2018.
  
• workshop
  Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease
  D. Pace, A.V. Dalca, T.Brosch, T.Geva, A.J. Powell, J. Weese, M.H. Moghari, P. Golland.
  MICCAI DLMIA: Deep Learning in Medical Image Analysis. 2018.
  [ arXiv preprint ]
• workshop
  Spatial Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation
  A.V. Dalca, J. Guttag, M. R. Sabuncu.
  NeurIPS ML4H: Machine Learning for Health. 2017.
  [ Spotlight ]
• workshop
  Patch-Based Discrete Registration of Clinical Brain Images.
  A.V. Dalca, A. Bobu, N.S. Rost, P. Golland.
  MICCAI PATCHMI: Patch-based Techniques in Medical Imaging, LNCS 9993, pp 60-67, 2016.
  [ paper | code | Best paper award ]
• workshop
  tipiX: Rapid Visualization of Large Image Collections
  A.V. Dalca, R. Sridharan, N.S. Rost, P. Golland.
  MICCAI IMIC: Interactive Medical Image Computing Workshop, 2014.
  [ paper | Video ]
  [ Best paper award for impact and usability | Finalist CSAIL Amazing Research Highlight Competition | Oral Presentation ]
• workshop
  An interactive visualization tool for Nipype medical imaging pipelines
  R. Sridharan, A.V. Dalca, P. Golland.
  MICCAI IMIC: Interactive Medical Image Computing Workshop, 2014.
  [ paper | Oral Presentation ]
• workshop
  Quantification and Analysis of Large Multimodal Clinical Image Studies: Application to Stroke
  R. Sridharan^‡, A.V. Dalca^‡, K.M. Fitzpatrick, L. Cloonan, A. Kanakis, O. Wu, K.L. Furie, J. Rosand, N.S. Rost, P. Golland.
  MICCAI MBIA International Workshop on Multimodal Brain Image Analysis (MBIA), pp. 18–30, 2013.
  [ paper | doi | ^‡ equal contribution | Oral Presentation ]

Theses

• thesis
  Genetic, Clinical and Population Priors for Brain Images
  A.V. Dalca.
  Ph.D. Thesis, Massachusetts Institute of Technology, 2016.
  [ PDF ]
• thesis
  Segmentation of Nerve Bundles and Ganglia in Spine MRI using Particle Filters
  A.V. Dalca
  S.M. Thesis, Massachusetts Institute of Technology, 2012.
  [ PDF | Morris Joseph Levin Award for best thesis presentation at Masterworks ]

Books and Proceedings

• Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis
  C.H. Sudre, H. Fehri, H., T. Arbel, C.F. Baumgartner, A. V. Dalca, et al (Editors).
  Springer. 2020.
  [ Book link ]
• NeurIPS Machine Learning for Health Workshop
  A. V. Dalca, M. B.A. McDermott, E. Alsentzer, S. G. Finlayson, M. Oberst, F. Falck, C. Chivers, A. Beam, T. Naumann, B. Beaulieu-jones (Editors).
  PMLR. 2020.
  [ Proceedings | Introduction | citation bib"]
• Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures
  H. Greenspan, R. Tanno, M. Erdt, T. Arbel, C. Baumgartner, A. V. Dalca, et al (Editors).
  Springer. 2019.
  [ Book link ]
• Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities
  D. Stoyanov, Z.Taylor, E. Ferrante, A. V. Dalca, et al (Editors).
  Springer. 2018.
  [ Book link ]
• Imaging Genetics
  A.V. Dalca, N.K. Batmanghelich, M.R. Sabuncu, L. Shen (Editors).
  Elsevier. 2017.
  [ Book link ]
• Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics
  J. Cardoso, T. Arbel, E. Ferrante, X. Pennec, A.V. Dalca, et al (Editors).
  Springer. 2017.
  [ Book link ]
• Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, Stroke Imaging and Treatment
  J. Cardoso, T. Arbel, F. Gao, B. Kainz, T. van Walsum, K. Shi, K.K. Bhatia, R. Peter, T. Vercauteren, M. Reyes, A.V. Dalca, et al (Editors)
  Springer. 2017.
  [ Book link ]