InsMix: Towards Realistic Generative Data Augmentation for Nuclei
Instance Segmentation

InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance Segmentation

30 June 2022

Kwang-Ting Cheng

Hao Chen

Papers citing "InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance Segmentation"

7 / 7 papers shown

Title
Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Model Seonghui Min Hyunwoo Oh Won-Ki Jeong DiffM MedIm 42 4 0 19 Jul 2024
URCDM: Ultra-Resolution Image Synthesis in Histopathology Sarah Cechnicka James G. C. Ball Matthew Baugh Hadrien Reynaud Naomi Simmonds A. Smith Catherine Horsfield C. Roufosse Bernhard Kainz MedIm 31 1 0 18 Jul 2024
Deep Learning for Computational Cytology: A Survey Hao Jiang Yanning Zhou Yi-Mou Lin R. Chan Jiangshu Liu Hao Chen 19 75 0 10 Feb 2022
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Huayu Chen A. Srinivas Rui Qian Nayeon Lee E. D. Cubuk Quoc V. Le Barret Zoph ISeg 252 969 0 13 Dec 2020
Instance-aware Self-supervised Learning for Nuclei Segmentation Xinpeng Xie Jiawei Chen Yuexiang Li Linlin Shen Kai Ma Yefeng Zheng SSL 108 59 0 22 Jul 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 295 10,618 0 19 Feb 2017
Image-to-Image Translation with Conditional Adversarial Networks Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros SSeg 212 19,450 0 21 Nov 2016