ErrorNet: Learning error representations from limited data to improve vascular segmentation

10 October 2019

Papers citing "ErrorNet: Learning error representations from limited data to improve vascular segmentation"

4 / 4 papers shown

Title
R2U++: A Multiscale Recurrent Residual U-Net with Dense Skip Connections for Medical Image Segmentation Mehreen Mubashar Hazrat Ali C. Grönlund Shoaib Azmat SSeg 21 66 0 03 Jun 2022
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation Zongwei Zhou M. R. Siddiquee Nima Tajbakhsh Jianming Liang SSeg 22 2,565 0 11 Dec 2019
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Nima Tajbakhsh Laura Jeyaseelan Q. Li J. Chiang Zhihao Wu Xiaowei Ding 16 750 0 27 Aug 2019
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy Christian Wachinger M. Reuter T. Klein 3DV 29 330 0 27 Feb 2017