Michael A. Jacobs

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 19

Top Topics

Data Visualization

Landmark Localization

Medical Imaging

Dimensionality Reduction

Top Venues

IEEE Trans. Aerosp. Electron. Syst.

Publications

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) (2024)
Guangyao Zheng, Shuhao Lai, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh
Multi-environment lifelong deep reinforcement learning for medical imaging. CoRR (2023)
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)
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 (2023)
Guangyao Zheng, Michael A. Jacobs, Vladimir Braverman, Vishwa S. Parekh
Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging. CoRR (2023)
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 (2023)
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 (2021)
Vishwa S. Parekh, Alex E. Bocchieri, Vladimir Braverman, Michael A. Jacobs
Multitask radiological modality invariant landmark localization using deep reinforcement learning. MIDL (2020)
Vishwa S. Parekh, Michael A. Jacobs
Tumor Connectomics: Mapping the intra-tumoral complex interaction network. CoRR (2019)
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 (2019)
Vishwa S. Parekh, Michael A. Jacobs
Radiomic Synthesis Using Deep Convolutional Neural Networks. ISBI (2019)
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 (2019)
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 (2018)
Vishwa S. Parekh, Michael A. Jacobs
MPRAD: A Multiparametric Radiomics Framework. CoRR (2018)
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 (2018)
Vishwa S. Parekh, Michael A. Jacobs
Radiomic Synthesis Using Deep Convolutional Neural Networks. CoRR (2018)
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 (2018)
Vishwa S. Parekh, Michael A. Jacobs
A multidimensional data visualization and clustering method: Consensus similarity mapping. ISBI (2016)
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 (2016)
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)
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)
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)
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)
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) (2003)
Amir Ghanei, Hamid Soltanian-Zadeh, Michael A. Jacobs
Boundary-based warping of brain MR images. Medical Imaging: Image Processing (2000)