Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels

3 March 2022

Papers citing "Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels"

9 / 9 papers shown

Title
RobustEMD: Domain Robust Matching for Cross-domain Few-shot Medical Image Segmentation Yazhou Zhu Minxian Li Qiaolin Ye Shidong Wang Tong Xin Haofeng Zhang 30 0 0 01 Oct 2024
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models Lin Zhao Xiao Chen Eric Z. Chen Yikang Liu Terrence Chen Shanhui Sun VLM 54 5 0 16 Aug 2024
Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation Yazhou Zhu Shidong Wang Tong Xin Zheng-Wei Zhang Haofeng Zhang 12 10 0 20 Sep 2023
Efficient Subclass Segmentation in Medical Images Linrui Dai Wenhui Lei Xiaofan Zhang 11 1 0 01 Jul 2023
AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection M. Astaraki F. Benetti Yousef Yeganeh I. Toma-Dasu Orjan Smedby Chunliang Wang Nassir Navab T. Wendler 6 6 0 21 May 2023
CRNet: Cross-Reference Networks for Few-Shot Segmentation Weide Liu Chi Zhang Guosheng Lin Fayao Liu SSeg 141 190 0 24 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,568 0 09 Mar 2017
Superpixels: An Evaluation of the State-of-the-Art David Stutz Alexander Hermans Bastian Leibe SupR 61 468 0 06 Dec 2016
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,106 0 16 Nov 2016