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ORCIDMichael A. Jacobs
Person information
- affiliation: Johns Hopkins University, Department of Radiology, Baltimore, MD; USA
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2020 – today
- 2024
[j2]Emily R. Bartusiak
, Michael A. Jacobs, Moses W. Chan, Mary L. Comer, Edward J. Delp:
Predicting Hypersonic Glide Vehicle Behavior With Stochastic Grammars. IEEE Trans. Aerosp. Electron. Syst. 60(1): 1208-1223 (2024)- 2023
- [c9]Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa Sanjay Parekh:
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. MIDL 2023: 1751-1764 - [i14]Guangyao Zheng, Samson Zhou, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh:
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging. CoRR abs/2302.11510 (2023) - [i13]Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman, Vishwa S. Parekh:
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging. CoRR abs/2303.06783 (2023) - [i12]Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh:
Multi-environment lifelong deep reinforcement learning for medical imaging. CoRR abs/2306.00188 (2023) - [i11]Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh:
A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments. CoRR abs/2306.05310 (2023) - 2021
- [i10]Vishwa S. Parekh, Shuhao Lai, Vladimir Braverman, Jeff Leal, Steven Rowe, Jay J. Pillai, Michael A. Jacobs:
Cross-Domain Federated Learning in Medical Imaging. CoRR abs/2112.10001 (2021) - 2020
- [c8]Vishwa S. Parekh, Alex E. Bocchieri, Vladimir Braverman, Michael A. Jacobs:
Multitask radiological modality invariant landmark localization using deep reinforcement learning. MIDL 2020: 588-600
2010 – 2019
- 2019
- [c7]Vishwa S. Parekh, Michael A. Jacobs:
Radiomic Synthesis Using Deep Convolutional Neural Networks. ISBI 2019: 1114-1117 - [i9]Vishwa S. Parekh, Michael A. Jacobs:
Tumor Connectomics: Mapping the intra-tumoral complex interaction network. CoRR abs/1901.09861 (2019) - [i8]Vishwa S. Parekh, John Laterra, Chetan Bettegowda, Alex E. Bocchieri, Jay J. Pillai, Michael A. Jacobs:
Multiparametric Deep Learning and Radiomics for Tumor Grading and Treatment Response Assessment of Brain Cancer: Preliminary Results. CoRR abs/1906.04049 (2019) - [i7]Alex E. Bocchieri, Vishwa S. Parekh, Kathryn R. Wagner, Shivani Ahlawat, Vladimir Braverman, Doris G. Leung, Michael A. Jacobs:
Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results. CoRR abs/1908.00175 (2019) - 2018
- [i6]Vishwa S. Parekh, Katarzyna J. Macura, Susan C. Harvey, Ihab Kamel, Riham El Khouli, David A. Bluemke, Michael A. Jacobs:
Multiparametric Deep Learning Tissue Signatures for a Radiological Biomarker of Breast Cancer: Preliminary Results. CoRR abs/1802.08200 (2018) - [i5]Sanghyun Choi, Nikita Ivkin, Vladimir Braverman, Michael A. Jacobs:
DreamNLP: Novel NLP System for Clinical Report Metadata Extraction using Count Sketch Data Streaming Algorithm: Preliminary Results. CoRR abs/1809.02665 (2018) - [i4]Vishwa S. Parekh, Michael A. Jacobs:
MPRAD: A Multiparametric Radiomics Framework. CoRR abs/1809.09973 (2018) - [i3]Vishwa S. Parekh, Michael A. Jacobs:
Radiomic Synthesis Using Deep Convolutional Neural Networks. CoRR abs/1810.11090 (2018) - [i2]Michael A. Jacobs, Christopher Umbricht, Vishwa S. Parekh, Riham El Khouli, Leslie Cope, Katarzyna J. Macura, Susan C. Harvey, Antonio C. Wolff:
Advanced machine learning informatics modeling using clinical and radiological imaging metrics for characterizing breast tumor characteristics with the OncotypeDX gene array. CoRR abs/1811.03218 (2018) - 2016
- [c6]Vishwa S. Parekh, Michael A. Jacobs:
A multidimensional data visualization and clustering method: Consensus similarity mapping. ISBI 2016: 420-423 - [i1]Vishwa S. Parekh, Jeremy R. Jacobs, Michael A. Jacobs:
Unsupervised Non Linear Dimensionality Reduction Machine Learning methods applied to Multiparametric MRI in cerebral ischemia: Preliminary Results. CoRR abs/1606.03788 (2016) - 2014
- [c5]Vishwa S. Parekh, Jeremy R. Jacobs, Michael A. Jacobs:
Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results. Medical Imaging: Image Processing 2014: 90342O - 2011
- [c4]Ahmed A. Harouni, Michael A. Jacobs, Nael F. Osman:
Finding the Optimal Compression Level for Strain-Encoded (SENC) Breast MRI; Simulations and Phantom Experiments. MICCAI (1) 2011: 444-451
2000 – 2009
- 2003
- [j1]Torsten Rohlfing, Calvin R. Maurer Jr., David A. Bluemke, Michael A. Jacobs:
Volume-Preserving Non-Rigid Registration of MR Breast Images Using Free-Form Deformation with an Incompressibility Constraint. IEEE Trans. Medical Imaging 22(6): 730-741 (2003) - [c3]Torsten Rohlfing, Calvin R. Maurer Jr., David A. Bluemke, Michael A. Jacobs:
Volumenerhaltende elastische Registrierung. Evaluierung mit klinischen MR-Mammographien. Bildverarbeitung für die Medizin 2003: 91-95 - [c2]Torsten Rohlfing, Calvin R. Maurer Jr., David A. Bluemke, Michael A. Jacobs:
An Alternating-Constraints Algorithm for Volume-Preserving Non-rigid Registration of Contrast-Enhanced MR Breast Images. WBIR 2003: 291-300 - 2000
- [c1]Amir Ghanei, Hamid Soltanian-Zadeh, Michael A. Jacobs:
Boundary-based warping of brain MR images. Medical Imaging: Image Processing 2000
Coauthor Index
aka: Vishwa Sanjay Parekh
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