Q
Qiu Huang
Researcher at Shanghai Jiao Tong University
Publications - 6
Citations - 67
Qiu Huang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Median filter & Medicine. The author has an hindex of 3, co-authored 4 publications receiving 57 citations.
Papers
More filters
Journal ArticleDOI
Dictionary learning based impulse noise removal via L1-L1 minimization
Shanshan Wang,Shanshan Wang,Qiegen Liu,Qiegen Liu,Yong Xia,Pei Dong,Jianhua Luo,Qiu Huang,David Dagan Feng,David Dagan Feng +9 more
TL;DR: The results suggest that DL-INR has a better ability to suppress impulse noise than other six algorithms and can produce restored images with higher peak signal-to-noise ratio (PSNR).
Proceedings ArticleDOI
Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints
TL;DR: The results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.
Journal ArticleDOI
Bias correction for magnetic resonance images via joint entropy regularization.
Shanshan Wang,Shanshan Wang,Yong Xia,Yong Xia,Pei Dong,Jianhua Luo,Qiu Huang,Dagan Feng,Dagan Feng,Yuanxiang Li +9 more
TL;DR: To effectively restore the original signal, this paper simultaneously exploits the spatial and gradient features of the corrupted MR images for bias correction via the joint entropy regularization.
Journal ArticleDOI
Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization
Xiaoya Qiao,Chunjuan Jiang,Panli Li,Yuan Yuan,Qinglong Zeng,Lei Bi,Shaoli Song,Jinman Kim,Dagan Feng,Qiu Huang +9 more
TL;DR: An attentive transformation (AT)-based normalization method for PET tumor segmentation that exploits the distinguishability of breast tumor in PET images and dynamically generate dedicated and pixel-dependent learnable parameters in normalization via the transformation on a combination of channel-wise and spatial-wise attentive responses.
Journal ArticleDOI
A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging.
Wenxiang Ding,Qiaoqiao Ding,Kewei Chen,Miao Zhang,Li Lv,David Dagan Feng,Lei Bi,Jinman Kim,Qiu Huang +8 more
TL;DR: In this article , a modified Logan reference plot model was proposed to shorten the acquisition procedure in dynamic PET imaging by omitting the early-time information necessary for the conventional reference Logan model.