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Medical Image Analysis|December 20, 2020
Test-time adaptable neural networks for robust medical image segmentationNeerav Karani, Ertunc Erdil, Krishna Chaitanya, et al.Medical Image Analysis|April 13, 2023
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentationKrishna Chaitanya, Ertunc Erdil, Neerav Karani, et al.Medical Image Analysis|January 1, 2021
Semi-supervised task-driven data augmentation for medical image segmentationKrishna Chaitanya, Neerav Karani, Christian F Baumgartner, et al.IEEE Transactions on Medical Imaging|July 12, 2018
Reducing Navigators in Free-Breathing Abdominal MRI via Temporal Interpolation Using Convolutional Neural NetworksNeerav Karani, Christine Tanner, Sebastian Kozerke, et al.Medical Image Analysis|March 3, 2019
An image interpolation approach for acquisition time reduction in navigator-based 4D MRINeerav Karani, Lin Zhang, Christine Tanner, et al.IEEE Transactions on Medical Imaging|February 10, 2022
Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned PriorKerem C Tezcan, Neerav Karani, Christian F Baumgartner, et al.Investigative Radiology|June 2, 2021
Whole-body Composition Profiling Using a Deep Learning Algorithm: Influence of Different Acquisition Parameters on Algorithm Performance and RobustnessFlorian A Huber, Krishna Chaitanya, Nico Gross, et al.Bioinformatics (Oxford, England)|August 26, 2010
Obtaining better quality final clustering by merging a collection of clusteringsSelim Mimaroglu, Ertunc ErdilEuropean Journal of Radiology|November 11, 2019
Variability of manual segmentation of the prostate in axial T2-weighted MRI: A multi-reader studyAnton S Becker, Krishna Chaitanya, Khoschy Schawkat, et al.Pageof 38