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Rethinking Semi-Supervised Medical Image Segmentation: A
  Variance-Reduction Perspective

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

3 February 2023
Chenyu You
Weicheng Dai
Yifei Min
Fenglin Liu
David A. Clifton
S. Kevin Zhou
Lawrence H. Staib
James S Duncan
ArXivPDFHTML

Papers citing "Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective"

16 / 16 papers shown
Title
COMMA: Coordinate-aware Modulated Mamba Network for 3D Dispersed Vessel Segmentation
Gen Shi
Hui Zhang
Jie Tian
Mamba
66
0
0
04 Mar 2025
Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning
Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning
Yuting He
Boyu Wang
Rongjun Ge
Yang Chen
Guanyu Yang
Shuo Li
MedIm
AAML
62
2
0
07 Feb 2025
SegICL: A Multimodal In-context Learning Framework for Enhanced
  Segmentation in Medical Imaging
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging
Lingdong Shen
Fangxin Shang
Xiaoshuang Huang
Yehui Yang
Haifeng Huang
Shiming Xiang
VLM
31
3
0
25 Mar 2024
Multimodal Prompt Learning for Product Title Generation with Extremely
  Limited Labels
Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels
Bang-ju Yang
Fenglin Liu
Zheng Li
Qingyu Yin
Chenyu You
Bing Yin
Yuexian Zou
VLM
26
5
0
05 Jul 2023
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask
  Generation
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation
Kun Han
Yifeng Xiong
Chenyu You
Pooya Khosravi
Shanlin Sun
Xiangyi Yan
James Duncan
Xiaohui Xie
MedIm
DiffM
30
20
0
08 Apr 2023
Implicit Anatomical Rendering for Medical Image Segmentation with
  Stochastic Experts
Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts
Chenyu You
Weicheng Dai
Yifei Min
Lawrence H. Staib
James S. Duncan
MedIm
67
27
0
06 Apr 2023
Learning with Limited Annotations: A Survey on Deep Semi-Supervised
  Learning for Medical Image Segmentation
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation
Rushi Jiao
Yichi Zhang
Leiting Ding
Rong Cai
Jicong Zhang
21
151
0
28 Jul 2022
Pessimism in the Face of Confounders: Provably Efficient Offline
  Reinforcement Learning in Partially Observable Markov Decision Processes
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
Miao Lu
Yifei Min
Zhaoran Wang
Zhuoran Yang
OffRL
45
22
0
26 May 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
302
7,434
0
11 Nov 2021
Mutual Consistency Learning for Semi-supervised Medical Image
  Segmentation
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation
Yicheng Wu
Z. Ge
Donghao Zhang
Minfeng Xu
Lei Zhang
Yong-quan Xia
Jianfei Cai
OOD
SSL
67
230
0
21 Sep 2021
On Feature Decorrelation in Self-Supervised Learning
On Feature Decorrelation in Self-Supervised Learning
Tianyu Hua
Wenxiao Wang
Zihui Xue
Sucheng Ren
Yue Wang
Hang Zhao
SSL
OOD
117
187
0
02 May 2021
Every Annotation Counts: Multi-label Deep Supervision for Medical Image
  Segmentation
Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation
Simon Reiß
C. Seibold
Alexander Freytag
E. Rodner
Rainer Stiefelhagen
85
61
0
27 Apr 2021
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
279
0
12 Feb 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
252
3,369
0
09 Mar 2020
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
244
1,275
0
06 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
261
9,136
0
06 Jun 2015
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