no code implementations • Findings (EMNLP) 2021 • An Yan, Zexue He, Xing Lu, Jiang Du, Eric Chang, Amilcare Gentili, Julian McAuley, Chun-Nan Hsu
Radiology report generation aims at generating descriptive text from radiology images automatically, which may present an opportunity to improve radiology reporting and interpretation.
no code implementations • 5 Aug 2019 • Michal Byra, Mei Wu, Xiaodong Zhang, Hyungseok Jang, Ya-Jun Ma, Eric Y Chang, Sameer Shah, Jiang Du
Next, the T1, T1$\rho$, T2* relaxations, and ROI areas were determined for the manual and automatic segmentations, then compared. The models developed using ROIs provided by two radiologists achieved high Dice scores of 0. 860 and 0. 833, while the radiologists' manual segmentations achieved a Dice score of 0. 820.
1 code implementation • 1 Feb 2018 • Jiang Du, Xuemei Xie, Chenye Wang, Guangming Shi
In detail, we employ perceptual loss, defined on feature level, to enhance the structure information of the recovered images.
1 code implementation • 1 Feb 2018 • Xuemei Xie, Chenye Wang, Jiang Du, Guangming Shi
In measurement part, the input image is adaptively measured block by block to acquire a group of measurements.
1 code implementation • 21 Nov 2017 • Jiang Du, Xuemei Xie, Chenye Wang, Guangming Shi, Xun Xu, Yu-Xiang Wang
Recently, deep learning methods have made a significant improvement in compressive sensing image reconstruction task.
1 code implementation • 23 Sep 2017 • Xuemei Xie, Yu-Xiang Wang, Guangming Shi, Chenye Wang, Jiang Du, Zhifu Zhao
In this paper, we propose an adaptive measurement network in which measurement is obtained by learning.