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

Peer Reviewed Publications

• 2023
• conference
  Scale-Space Hypernetworks for Efficient Biomedical Image Analysis.
  J.J.G. OrtizJ. Guttag, A. V. Dalca
  NeurIPS: Advances in Neural Information Processing Systems. Accepted. 2023.
  [ arxiv ]
• conference
  UniverSeg: Universal Medical Image Segmentation.
  V.I. Butoi*, J.J.G. Ortiz*, T.Ma, M.R. Sabuncu, J. Guttag, A. V. Dalca
  ICCV: International Conference on Computer Vision. Accepted. 2023.
  [ arxiv | website | tutorial | code ]
• conference
  Neuralizer: Neuroimage Analysis without Re-Training.
  S. Czolbe, A. V. Dalca
  CVPR: Computer Vision and Pattern Recognition. pp. 6217-6230. 2023.
  [ arXiv preprint ]
• conference
  Joint cortical registration of geometry and function using semi-supervised learning.
  J. Li, G. Tuckute, E. Fedorenko, B. L. Edlow, B. Fischl^‡, A. V. Dalca^‡
  MIDL: Medical Imaging with Deep Learning. pp. 1-15. 2023.
  [ arXiv preprint ]
• conference
  Anatomy-specific acquisition-agnostic affine registration learned from fictitious images.
  M. Hoffmann, A. Hoopes, B. Fischl^‡, A. V. Dalca^‡
  Proc. SPIE: Medical Imaging 2023: Image Processing. 1246402. 2023.
  [ SPIE paper ]
• conference
  AngioMoCo: Learning-based Motion Correction in Digital Subtraction Angiography.
  R. Su, P. van der Sluijs, S. Cornelissen, W. van Zwam, A. van der Lugt, W. Niessen, D. Ruijters, T. van Walsum, A. V. Dalca
  MICCAI: Medical Image Computing and Computer-Assisted Intervention. Accepted. 2023.
  
• journal
  SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining.
  B. Billot, D. Greve, O. Puonti, A. Thielscher, K. Van Leemput, B. Fischl, A. V. Dalca, J. E. Iglesias
  MedIA: Medical Image Analysis, 86. 102789. 2023.
  [ paper | arXiv preprint ]
• journal
  A robust and interpretable deep learning framework for multi-modal registration via keypoints .
  A. Q. Wang, E. M. Yu, A. V. Dalca M. R. Sabuncu
  MedIA: Medical Image Analysis. 102962. 2023.
  [ arXiv preprint ]
• journal
  Supervision by Denoising.
  S. I. Young, A. V. Dalca, E. Ferrante, P. Golland, C. A. Metzler, B. Fischl, J. E. Iglesias
  IEEE TPAMI: Transactions on Pattern Analysis and Machine Intelligence -- ICCP Special Issue, 2023.
  [ arxiv ]
• journal
  Hyper-Convolutions via Implicit Kernels for Medical Image Analysis.
  T. Ma, A.Q. Wang, A. V. Dalca, M.R. Sabuncu
  MedIA: Medical Image Analysis, 86. 102796. 2023.
  [ arXiv preprint ]
• conference
  Data Consistent Deep Rigid MRI Motion Correction.
  N. M. Singh, N. Dey, M. Hoffmann, B. Fischl, E. Adalsteinsson, R. Frost, A. V. Dalca, P. Golland
  MIDL: Medical Imaging with Deep Learning. 177. pp. 1-14. 2023.
  [ arXiv preprint | Oral Presentation | Best Presentation Award ]
• conference
  AnyStar: Domain randomized universal star-convex 3D instance segmentation.
  N. Dey, S.M. Abulnaga, B. Billot, E.A. Turk, P.E. Grant, A.V. Dalca, P. Golland
  WACV: Winter Conference on Applications of Computer Vision. 2023
  [ arXiv prepreint ]
• journal
  A cellular resolution atlas of Broca's area.
  I. Costantini, L. Morgan, J. Yang, Y. Balbastre, et al (39 authors)
  AAAS Scientific Advances, In Press, 2023.
   
• 2022
• conference
  TopoFit: Rapid Reconstruction of Topologically-Correct Cortical Surfaces.
  A. Hoopes, J. E. Iglesias, B. Fischl, D. Greve^‡, A. V. Dalca^‡
  MIDL: Medical Imaging with Deep Learning. Accepted. 2022.
  [ Open Review | Oral Presentation ]
• journal
  SynthMorph: learning contrast-invariant registration without acquired images.
  M. Hoffmann, B. Billot, D.N. Greve, J.E. Iglesias, B. Fischl, A.V. Dalca
  IEEE TMI: Transactions on Medical Imaging. 41(3). pp. 543-558. 2022.
  [ website | arXiv preprint | video ]
• journal
  Learning the Effect of Registration Hyperparameters with HyperMorph.
  A. Hoopes, M. Hoffmann, D.N. Greve, B. Fischl, J. Guttag, A.V. Dalca
  MELBA: Machine Learning for Biomedical Imaging. 3. pp. 1-30. 2022.
  [ arXiv preprint ]
• conference
  KeyMorph: Robust Multi-modal Affine Registration via Unsupervised Keypoint Detection .
  E. M. Yu, A. Q. Wang, A. V. Dalca^‡ M. R. Sabuncu^‡
  MIDL: Medical Imaging with Deep Learning. PMLR 121. pp 75-93. 2022.
  [ Open Review | Oral Presentation ]
• journal
  Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis.
  N.M. Singh, J.E. Iglesias, E. Adalsteinsson, A.V. Dalca, P. Golland
  MELBA: Machine Learning for Biomedical Imaging. 1. pp 1-28. 2022.
  [ arXiv preprint | paper ]
• journal
  Computing Multiple Image Reconstructions with a Single Hypernetwork.
  A.Q. Wang, A.V. Dalca, M. R. Sabuncu
  MELBA: Machine Learning for Biomedical Imaging. Accepted. 2022.
  [ arXiv preprint ]
• journal
  SynthStrip: Skull-Stripping for Any Brain Image.
  Andrew Hoopes, Jocelyn S. Mora, A.V. Dalca, Bruce Fischl ^‡, Malte Hoffmann ^‡
  Neuroimage. Accepted. 2022.
  [ arXiv preprint | website | ^‡ equal contribution ]
• journal
  Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease.
  D. Pace, A.V. Dalca, T. Brosch, T.Geva, A.J. Powell, J. Weese, M.H. Moghari, P. Golland.
  MedIA: Medical Image Analysis, 80, pp. 102469, 2022.
  [ paper ]
• journal
  Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.
  A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, . . . . ., A.V. Dalca, M. P. Heinrich.
  IEEE TMI: Transactions on Medical Imaging, 42, (3), pp. 697-712, 2022.
  [ arXiv preprint ]
• journal
  Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration.
  E. Mu, S. Jabbour, A. V. Dalca, J. Guttag, J. Wiens, M.W. Sjoding
  Plos one 17 (2), e0263922. 2022.
  [ Paper ]
• journal
  Mapping the subcortical connectivity of the human default mode network.
  J. Li, W.H. Curley, B. Guerin, D.D. Dougherty,A.V. Dalca, B. Fischl, A. Horn, B.L. Edlow.
  Neuroimage 245, 118758. 2021.
  [ Paper ]
• journal
  Sex-specific lesion pattern of functional outcomes after stroke.
  A Bonkhoff, M Bretzner, S Hong, M Schirmer, A Cohen, R Regenhardt, K Donahue, M Nardin, A.V. Dalca, et al (58 authors)
  Brain communications 4.2. 2022.
  [ Paper ]
• 2021
• 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. 12729. pp. 3-17. 2021.
  [ website | arXiv preprint | Oral Presentation (video) | Runner up: Erbsmann prize. | website ]
• conference
  Learning MRI contrast-agnostic registration.
  M. Hoffmann, B. Billot, J.E. Iglesias, B. Fischl, A.V. Dalca
  ISBI: International Symposium on Biomedical Imaging. pp. 899-903. 2021
  [ Oral Presentation (video) ]
• conference
  Hyper-Convolution Networks for Biomedical Image Segmentation.
  T. Ma, A.V. Dalca, M. Sabuncu
  WACV: Winter Conference on Applications of Computer Vision. pp. 1933-1942. 2022
  [ arXiv prepreint ]
• conference
  Generative Adversarial Registration for Improved Conditional Deformable Templates.
  N. Dey, M. Ren, A.V. Dalca, G. Gerig
  ICCV: International Conference on Computer Vision. pp 3929-3941. 2021
  [ arXiv preprint ]
• conference
  End-to-End Sequential Sampling and Reconstruction for MR Imaging.
  T. Yin, Z. Wu, H. Sun, A.V. Dalca, Y. Yue, K.L. Bouman
  ML4H: Machine Learning for Health. PMLR 158:261-281. 2021
  [ arXiv preprint | Oral Presentation. | Best Paper Award. | website ]
• 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.
  [ arXiv preprint ]
• 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. pp. 1971-1974. 2021.
  [ Oral Presentation ]
• journal
  A Deep Learning Toolbox for Automatic Segmentation of Subcortical Limbic Structures from MRI Images.
  D. N. Greve, B. Billot, D. Cordero, A. Hoopes, M. Hoffmann, A.V. Dalca, B. Fischl, J. E. Iglesias, J. C. Augustinack
  NeuroImage. 118610. 2021
  
• journal
  Mapping the subcortical connectivity of the human default mode network.
  J. Li, W.H. Curley, B. Guerin, D.D. Dougherty, A.V. Dalca, B. Fischl, A. Horn, B.L. Edlow
  NeuroImage. In press. 2021
  
• journal
  MRI Radiomic signature of white matter hyperintensities is associated with clinical phenotypes.
  M. Bretzner, AK Bonkhoff, MD Schirmer, S Hong, A. V. Dalca, KL Donahue et al (55 authors)
  Frontiers Neuroscience. 15(691244). pp 1-11. 2021.
•   journal
  Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke
  S. Hong, Anne-K. Giese, M. D. Schirmer, A. K. Bonkhoff, M. Bretzner, P. Rist, A.V. Dalca, et al (56 authors)
  Frontiers in Neurology. 12(7000616). pp 1-10. 2021.
  [ Paper link ]
• journal
  Outcome after acute ischemic stroke is linked to sex-specific lesion patterns.
  A. K. Bonkhoff, M. D. Schirmer, M. Bretzner, S. Hong, R. W. Regenhardt, M. Brudfors, K. L. Donahue, M. J. Nardin, A. V. Dalca, et al (62 authors)
  Nature Communications. 12(3289). pp 1-14. 2021.
• journal
  Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer - ASEG and SAMSEG.
  D. Sederevicius, D. Vidal-Pineiro, O. Sorensen, K. van Leemput, J. E. Iglesias, A. V. Dalca, D. N. Greve, B. Fischl, A. Bjornerud, K. B. Walhovd, A. M. Fjell
  Neuroimage. 237. pp 1-14. 2021.
• 2020
• 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.
  
• 2019
• 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 Using Learned Transformations 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 ]
• 2018
• 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 | Finalist: Publication Impact (Young Scientist) Award 2022 | Finalist: Publication Impact (Young Scientist) Award 2023 ]
• 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 ]
• 2017 and earlier
• 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

• workshop
  Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging.
  H. Kim, V. Butoi, A. V. Dalca, M. Sabuncu
  MICCAI MedAGI: International Workshop on Foundation Models for General Medical AI. In Press. 2023.
• workshop
  UniverSeg: Universal Medical Image Segmentation.
  V. I. Butoi^‡, J.J.G. Ortiz ^‡, T. Ma, J. Guttag; M. Sabuncu, A. V. Dalca
  Med NeurIPS: Medical Imaging meets NeurIPS. Extended Abstract. 2022
• workshop
  Probabilistic Interactive Segmentation for any Medical Image.
  H. Wong, J. Guttag, A. V. Dalca
  Med NeurIPS: Medical Imaging meets NeurIPS. Extended Abstract. 2022
• workshop
  Contrast Invariant Feature Representations for Medical Image Analysis.
  Y.Z.R. Chua, A. V. Dalca
  Med NeurIPS: Medical Imaging meets NeurIPS. Extended Abstract. 2022
• workshop
  Region-of-Interest Adaptive Acquisition for Accelerated MRI.
  Z. Wu, T. Yin, A. V. Dalca, K. Bouman
  Med NeurIPS: Medical Imaging meets NeurIPS. Extended Abstract. 2022
• workshop
  3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images.
  S. Hong, R. Marinescu, A. V. Dalca, A. K. Bonkhoff, M. Bretzner, N. S. Rost, P. Golland
  MICCAI DGM: Generative Modeling of Three-Dimensional Medical Images. In Press. Springer. 2021.
  [ arXiv preprint ]
• workshop
  HyperRecon: Regularization-Agnostic CS-MRI Reconstruction with Hypernetworks.
  A.Q. Wang, A.V. Dalca, M. R. Sabuncu
  MICCAI MLMIR: Machine Learning for Medical Image Reconstruction. In Press. Springer. 2021.
  [ arXiv preprint ]
• 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 Perinatal Imaging, Placental and Preterm Image Analysis
  C.H. Sudre, R. Licandro, H., C.F. Baumgartner, A. Melbourne, A. V. Dalca, et al (Editors).
  Springer. 2021.
  [ Book link ]
• 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 ]