HySparK: Hybrid Sparse Masking for Large Scale Medical Image
Pre-Training

HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training

11 August 2024

S. Kevin Zhou

Papers citing "HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training"

6 / 6 papers shown

Title
Revisiting MAE pre-training for 3D medical image segmentation Tassilo Wald Constantin Ulrich Stanislav Lukyanenko Andrei Goncharov Alberto Paderno Leander Maerkisch Paul F. Jäger Paul F. Jäger Klaus Maier-Hein 37 2 0 30 Oct 2024
MobileUtr: Revisiting the relationship between light-weight CNN and Transformer for efficient medical image segmentation Fenghe Tang Bingkun Nian Jianrui Ding Quan Quan Jie-jin Yang Wei Liu S.Kevin Zhou ViT MedIm 18 3 0 04 Dec 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer Haonan Wang Peng Cao Jiaqi Wang Osmar R. Zaiane MedIm ViT 121 705 0 09 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 292 5,761 0 29 Apr 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 232 75,445 0 18 May 2015