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Krishna Chaitanya
Krishna Chaitanya
Data Scientist at Janssen R&D| Postdoc & Ph.D. & M.Sc. at ETH Zurich | B.E. at BITS-Pilani
Verified email at its.jnj.com - Homepage
Title
Cited by
Cited by
Year
Contrastive learning of global and local features for medical image segmentation with limited annotations
K Chaitanya, E Erdil, N Karani, E Konukoglu
Advances in Neural Information Processing Systems 33, 2020
4492020
Phiseg: Capturing uncertainty in medical image segmentation
CF Baumgartner, KC Tezcan, K Chaitanya, AM Hötker, UJ Muehlematter, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
1962019
Semi-supervised and Task-Driven Data Augmentation
K Chaitanya, N Karani, CF Baumgartner, A Becker, O Donati, ...
International Conference on Information Processing in Medical Imaging, 29-41, 2019
1592019
Test-time adaptable neural networks for robust medical image segmentation
N Karani, E Erdil, K Chaitanya, E Konukoglu
Medical Image Analysis 68, 101907, 2021
1412021
A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols
N Karani, K Chaitanya, C Baumgartner, E Konukoglu
arXiv preprint arXiv:1805.10170, 2018
1232018
Semi-supervised task-driven data augmentation for medical image segmentation
K Chaitanya, N Karani, CF Baumgartner, E Erdil, A Becker, O Donati, ...
Medical Image Analysis 68, 101934, 2021
952021
Learning to segment medical images with scribble-supervision alone
YB Can, K Chaitanya, B Mustafa, LM Koch, E Konukoglu, ...
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018
922018
The validity of RFID badges measuring face-to-face interactions
T Elmer, K Chaitanya, P Purwar, C Stadtfeld
Behavior research methods 51, 2120-2138, 2019
692019
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation
K Chaitanya, E Erdil, N Karani, E Konukoglu
Medical Image Analysis 87, 102792, 2023
622023
Variability of manual segmentation of the prostate in axial T2-weighted MRI: A multi-reader study
AS Becker, K Chaitanya, K Schawkat, UJ Muehlematter, AM Hötker, ...
European journal of radiology 121, 108716, 2019
582019
Contrastive learning of single-cell phenotypic representations for treatment classification
A Perakis, A Gorji, S Jain, K Chaitanya, S Rizza, E Konukoglu
Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021 …, 2021
282021
Imbalance-aware self-supervised learning for 3d radiomic representations
H Li, FF Xue, K Chaitanya, S Luo, I Ezhov, B Wiestler, J Zhang, B Menze
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
272021
Whole-body composition profiling using a deep learning algorithm: influence of different acquisition parameters on algorithm performance and robustness
FA Huber, K Chaitanya, N Gross, SR Chinnareddy, F Gross, E Konukoglu, ...
Investigative Radiology 57 (1), 33-43, 2022
102022
Explicitly Minimizing the Blur Error of Variational Autoencoders
G Bredell, K Flouris, K Chaitanya, E Erdil, E Konukoglu
arXiv preprint arXiv:2304.05939, 2023
92023
Task-agnostic out-of-distribution detection using kernel density estimation
E Erdil, K Chaitanya, N Karani, E Konukoglu
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2021
62021
Automatic planning of liver tumor thermal ablation using deep reinforcement learning
K Chaitanya, C Audigier, LE Balascuta, T Mansi
International Conference on Medical Imaging with Deep Learning, 219-230, 2022
42022
Unsupervised out-of-distribution detection using kernel density estimation
E Erdil, K Chaitanya, E Konukoglu
arXiv preprint arXiv:2006.10712, 2020
42020
A Field of Experts Prior for Adapting Neural Networks at Test Time
N Karani, G Brunner, E Erdil, S Fei, K Tezcan, K Chaitanya, E Konukoglu
arXiv preprint arXiv:2202.05271, 2022
32022
Accurate Medical Image Segmentation with Limited Annotations
K Chaitanya
ETH Zurich, 2022
12022
Robust medical image segmentation by adapting neural networks for each test image
N Karani, E Erdil, K Chaitanya, E Konukoglu
Medical Imaging with Deep Learning, 2021
2021
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