杜宏伟
个人信息
姓名：杜宏伟
民族：汉 籍贯：江苏徐州
联系电话：0551-63602493 电子邮箱：duhw@ustc.edu.cn
教育、工作经历
中国科学技术大学自动化系（本科）、中国科学技术大学电子科学与技术系（硕博）、
中国科学技术大学信息科学技术学院（教师）
科学研究
主要领域：生物医学成像、生物医学影像
具体方向：深度学习及压缩感知图像重建及处理；磁共振快速成像原理及算法；
谐波成像与高帧率成像原理及算法优化；先进生物医学成像系统等
科研项目
“基于3He极化的肺部低场磁共振成像专用设备研发”，国家自然科学基金重大仪器专项子课题，负责人；
“编码激励阵列换能器非线性声场特性及组织谐波成像研究”， 教育部青年创新基金项目，负责人；
“吸收媒质中非线性有限衍射波的理论、实验和计算仿真研究”， 国家自然科学基金青年基金项目，负责人
部分研究结果
头部磁共振图像欠采样重建（基于快速先验交替方向乘子法）：
心脏磁共振图像欠采样重建（基于交叠组合稀疏全变分模型）：
CT扫描图像相对定位（基于卷积神经网络模型）：
X-Ray骨龄检测系统（基于卷积神经网络模型）：
T1加权MRI图像脑龄预测（基于迁移学习方法）：
MRI快速图像重建（基于IKWI：图像-K空间-小波跨域模型）
有限衍射X波的非线性传播、吸收和波形畸变（基于KZK方程）：
近期学术论文
Fast compressed sensing MRI based on complex double-density dual-tree discrete wavelet transform, Shanshan Chen , Bensheng Qiu, Feng Zhao, Chao Li and Hongwei Du, International Journal of Biomedical Imaging，2017(2017) :1-13；
Compressed sensing MRI via fast linearized preconditioned alternating direction method of multipliers, Shanshan Chen , Hongwei Du, Linna Wu, Jiaquan Jin and Bensheng Qiu, BioMedical Engineering Online, 2017 16(53): 1-18；
Fast sparsity adaptive multipath matching pursuit for compressed sensing problems, Xiaofang Zhang, Hongwei Du, Bensheng Qiu and Shanshan Chen, Journal of Electronic Imaging, 2017 26(3):1-9；
Four-directional fractional-order total variation regularization for image denoising, Linna Wu,Yingping Chen, Jiaquan Jin, Hongwei Du, and Bensheng Qiu, Journal of Electronic Imaging, 2017 26(5):1-13；
A deep learning-based method for relative location prediction in CT scan images, Jiajia Guo , Hongwei Du, Bensheng Qiu, Xiao Liang, 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
Relative location prediction in CT scan images using convolutional neural networks，Guo JJ, Du HW, Qiu BS,Computer Methods and Programs in Biomedicine, 2018(160):43-49；
Compressed Sensing Reconstruction Based on Combination of Group Sparse Total Variation and Non-Convex Regularization, Yan T, Du HW, Qiu BS, Journalof Medical Imaging and Health Informatics,2018(8):1233-1242；
Constrained Higher Degree Total p-variation Minimization for MRI Reconstruction From Undersampled K-space Data, Jin JQ, DuHW, Qiu BS, Current Medical Imaging Reviews, 2018(14):995-1005
Compressed Sensing MRI via Extended Anisotropic and Isotropic Total Variation,Fanfan Zeng, Hongwei Du, Jiaquan Jin, Jinzhang Xu, and Bensheng Qiu, Journalof Medical Imagingand Health Informatics,2019(9):1-10；
Transfer learning on T1-weighted images for brain age estimation, Haitao Jiang, Jiajia Guo, Hongwei Du, Jinzhang Xuand Bensheng Qiu, Mathematical Biosciences and Engineering,2019 16(5):4382–4398
A bone age assessment system for real-world X-ray images based on convolutional neural networks, Jiajia Guo, Jianyue Zhu, Hongwei Du, Bensheng Qiu, Computers and Electrical Engineering，2020(81):1-13
IKWI-net: A cross-domain convolutional neural network for undersampled magnetic resonance image reconstruct- tion，Zhilun Wang, Haitao Jiang, Hongwei Du, Jinzhang Xu, Bensheng Qiu， Magnetic Resonance Imaging, 2020(73):1-10
Lightweight pyramid network with spatial attention mechanism for accurate retinal vessel segmentation，Tengfei Tan，Zhilun Wang，Hongwei Du，Jinzhang Xu，Bensheng Qiu，International Journal of Computer Assisted Radiology and Surgery, 2021(3):1-10
EF-Net：A novel enhancement and fusion network for RGB-D saliency detection，Qian Chen, Keren Fu, Ze Liu, Geng Chen, Hongwei Du, Bensheng Qiu, Ling Shao，Pattern Recognition，2021(112)：1-12
RGB-D Salient Object Detection via 3D Convolutional Neural Networks,Qian Chen, Ze Liu, Yi Zhang, Keren Fu, Qijun Zhao, Hongwei Du，Association for the Advancement of Artificial Intelligence (AAAI2021):1-9
DBGAN：A dual-branch generative adversarial network for undersampled MRI reconstruction，Xianzhe Liu, Hongwei Du, Jinzhang Xu, Bensheng Qiu，Magnetic Resonance Imaging，2022(89): 77-91
Boosting Medical Image Segmentation via Conditional-Synergistic Convolution and Lesion Decoupling，Huakun Yang, Qian Chen, Lei Zhu, Lujia Jin, Bensheng Qiu, Qiushi Ren, Hongwei Du, Yanye Lu，Computerized Medical Imaging and Graphics，accepted
获奖情况
“挑战杯”安徽省特等奖（“便携式超声成像系统”，指导教师）
首届安徽省高等学校教坛新秀奖