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Deepthi Rajashekar
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2020 – today
- 2023
- [j3]Alejandro Gutierrez, Anup Tuladhar, Matthias Wilms, Deepthi Rajashekar, Michael D. Hill, Andrew Demchuk, Mayank Goyal, Jens Fiehler, Nils D. Forkert:
Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Int. J. Comput. Assist. Radiol. Surg. 18(5): 827-836 (2023) - 2022
- [j2]Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert:
Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging. IEEE Trans. Medical Imaging 41(9): 2331-2347 (2022) - [c7]Alejandro Gutierrez, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert:
Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients. Medical Imaging: Computer-Aided Diagnosis 2022 - [c6]Samuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D. Forkert:
Stroke lesion localization in 3D MRI datasets with deep reinforcement learning. Medical Imaging: Computer-Aided Diagnosis 2022 - [c5]Emma A. M. Stanley, Deepthi Rajashekar, Pauline Mouches, Matthias Wilms, Kira Plettl, Nils D. Forkert:
A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder. Medical Imaging: Computer-Aided Diagnosis 2022 - [d1]Anup Tuladhar, Serena Schimert, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert:
Automatic Segmentation of Stroke Lesions in Non-contrast Computed Tomography Datasets with Convolutional Neural Networks. IEEE DataPort, 2022 - 2021
- [c4]Matthias Wilms, Pauline Mouches, Jordan J. Bannister, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert:
Towards Self-explainable Classifiers and Regressors in Neuroimaging with Normalizing Flows. MLCN@MICCAI 2021: 23-33 - [c3]Pauline Mouches, Matthias Wilms, Deepthi Rajashekar, Sönke Langner, Nils Daniel Forkert:
Unifying Brain Age Prediction and Age-Conditioned Template Generation with a Deterministic Autoencoder. MIDL 2021: 497-506 - 2020
- [j1]Anup Tuladhar, Serena Schimert, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert:
Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks. IEEE Access 8: 94871-94879 (2020) - [c2]Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert:
Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. MLCN/RNO-AI@MICCAI 2020: 23-33 - [i1]Matthias Wilms, Jordan J. Bannister, Pauline Mouches, M. Ethan MacDonald, Deepthi Rajashekar, Sönke Langner, Nils D. Forkert:
Bidirectional Modeling and Analysis of Brain Aging with Normalizing Flows. CoRR abs/2011.13484 (2020)
2010 – 2019
- 2016
- [c1]Deepthi Rajashekar, Nur Zincir-Heywood, Malcolm I. Heywood:
Smart Phone User Behaviour Characterization Based on Autoencoders and Self Organizing Maps. ICDM Workshops 2016: 319-326
Coauthor Index
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