Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

15 June 2017

Papers citing "Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation"

8 / 58 papers shown

Title
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation Radek Mackowiak Philip Lenz Omair Ghori Ferran Diego O. Lange Carsten Rother 26 108 0 23 Oct 2018
A Strategy of MR Brain Tissue Images' Suggestive Annotation Based on Modified U-Net Yang Deng Yao Sun Yongpei Zhu Mingwang Zhu Wei Han Kehong Yuan 11 13 0 19 Jul 2018
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy Firat Özdemir Z. Peng C. Tanner Philipp Fürnstahl O. Goksel 12 28 0 18 Jul 2018
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images S. Graham Hao Chen Jevgenij Gamper Qi Dou Pheng-Ann Heng David R. J. Snead Yee Wah Tsang Nasir M. Rajpoot MedIm 19 301 0 05 Jun 2018
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation L. Yang Yizhe Zhang Zhuo Zhao Hao Zheng Peixian Liang M. Ying A. Ahuja D. Z. Chen 16 31 0 02 Jun 2018
Learn the new, keep the old: Extending pretrained models with new anatomy and images Firat Özdemir Philipp Fürnstahl Orçun Göksel CLL 20 48 0 01 Jun 2018
Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation Ling Zhang Vissagan Gopalakrishnan Le Lu Ronald M. Summers J. Moss Jianhua Yao MedIm 21 38 0 25 Jan 2018
Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning Yang Nan Gianmarc Coppola Q. Liang Kunlin Zou Wei Sun Dan Zhang Yaonan Wang Guanzhen Yu 15 7 0 20 Dec 2017