22 citations · 23 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 1 cited
Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation
Xiaoqing Liu, Kengo Araki, Shota Harada +7
The domain shift in pathological segmentation is an important problem, where a network trained by a source domain (collected at a specific hospital) does not work well in the targe…
eess.IV2023
Mixing Data Augmentation with Preserving Foreground Regions in Medical Image Segmentation
Xiaoqing Liu, Kenji Ono, Ryoma Bise
The development of medical image segmentation using deep learning can significantly support doctors' diagnoses. Deep learning needs large amounts of data for training, which also r…
eess.IV2020★ 22 cited
GASNet: Weakly-supervised Framework for COVID-19 Lesion Segmentation
Zhanwei Xu, Yukun Cao, Cheng Jin +5
Segmentation of infected areas in chest CT volumes is of great significance for further diagnosis and treatment of COVID-19 patients. Due to the complex shapes and varied appearanc…