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SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation.

Y. He, V. Nath, D. Yang, Y. Tang, A. Myronenko, and D. Xu. MICCAI (4), volume 14223 of Lecture Notes in Computer Science, page 416-426. Springer, (2023)

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Martina Nath

Richa Nath

Miriam Nath

Jens Näth

Karl Nath

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Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples.J. Sun, Z. Xu, D. Yang, V. Nath, W. Li, C. Zhao, D. Xu, Y. Chen, and H. Roth. ICCV, page 5180-5189. IEEE, (2023)Semi-supervised Machine Learning with MixMatch and Equivalence Classes.C. Hansen, V. Nath, R. Gao, C. Bermudez, Y. Huo, K. Sandler, P. Massion, J. Blume, T. Lasko, and B. Landman. iMIMIC/MIL3ID/LABELS@MICCAI, volume 12446 of Lecture Notes in Computer Science, page 112-121. Springer, (2020)HyperSegNAS: Bridging One-Shot Neural Architecture Search with 3D Medical Image Segmentation using HyperNet.C. Peng, A. Myronenko, A. Hatamizadeh, V. Nath, M. Siddiquee, Y. He, D. Xu, R. Chellappa, and D. Yang. CVPR, page 20709-20719. IEEE, (2022)HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization.Y. Tang, Y. He, V. Nath, P. Guo, R. Deng, T. Yao, Q. Liu, C. Cui, M. Yin, Z. Xu and 4 other author(s). CoRR, (2024)VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge.V. Nath, W. Li, D. Yang, A. Myronenko, M. Zheng, Y. Lu, Z. Liu, H. Yin, Y. Law, Y. Tang and 12 other author(s). CoRR, (2024)Learning 3D White Matter Microstructure from 2D Histology.V. Nath, K. Schilling, S. Remedios, R. Bayrak, Y. Gao, J. Blaber, Y. Huo, B. Landman, and A. Anderson. ISBI, page 186-190. IEEE, (2019)The Power of Proxy Data and Proxy Networks for Hyper-parameter Optimization in Medical Image Segmentation.V. Nath, D. Yang, A. Hatamizadeh, A. Abidin, A. Myronenko, H. Roth, and D. Xu. MICCAI (3), volume 12903 of Lecture Notes in Computer Science, page 456-465. Springer, (2021)Warm Start Active Learning with Proxy Labels and Selection via Semi-supervised Fine-Tuning.V. Nath, D. Yang, H. Roth, and D. Xu. MICCAI (8), volume 13438 of Lecture Notes in Computer Science, page 297-308. Springer, (2022)A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-Weighted MRI.T. Yao, N. Newlin, P. Kanakaraj, V. Nath, L. Cai, K. Ramadass, K. Schilling, B. Landman, and Y. Huo. CDMRI@MICCAI, volume 14328 of Lecture Notes in Computer Science, page 13-22. Springer, (2023)Enabling Multi-shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE.V. Nath, I. Lyu, K. Schilling, P. Parvathaneni, C. Hansen, Y. Huo, V. Janve, Y. Gao, I. Stepniewska, A. Anderson and 1 other author(s). MICCAI (3), volume 11766 of Lecture Notes in Computer Science, page 573-581. Springer, (2019)

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Disambiguation of "Nath, Vishwesh"

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SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation.

Please choose a person to relate this publication to

Martina Nath

Richa Nath

Miriam Nath

Jens Näth

Karl Nath

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Nath, Vishwesh"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation.

Please choose a person to relate this publication to

Martina Nath

Richa Nath

Miriam Nath

Jens Näth

Karl Nath

Other publications of authors with the same name

Disambiguation

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SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation.