张息壤

基本信息

张息壤，人工智能与机器人学院人工智能系讲师、美国伊利诺伊理工学院电子工程专业博士，入选湖南省第十八批芙蓉海外高层次人才引进“百人计划”（青年），长期从事医学图像信号重建，医学图像检测与识别等领域研究。累计发表行业内高水平期刊会议论文10余篇。联系方式(Email)：xzhang@hutb.edu.cn

教育背景

2013-2017：东南大学，信息工程 工学学士

2019-2021：美国伊利诺伊理工学院，电子工程，理学硕士

2021-2025：美国伊利诺伊理工学院，电子工程，博士

工作履历

2025-至今：乐天使体育官网 专任教师

教授课程

本科生课程：《机器学习与深度学习》《智能语音信号处理》《计算机视觉》等
研究领域

医学图像信号重建：医学图像的运动补偿，医学图像的去噪，核医学图像的重建算法
医学图像检测与识别：医学图像的缺陷检测，医学图像的生理学指标自动测量与评估

科研项目

1.美国国立卫生研究院（NIH）项目“通过先进且临床实用的心肺运动校正和深度学习，优化心脏SPECT的诊断准确性、辐射剂量和患者吞吐量”（R01HL154687），参与。

2.美国国立卫生研究院（NIH）项目“改进儿科SPECT成像：通过先进的重建和运动校正技术提高病灶检出率并降低辐射剂量”（R01EB029315），参与。

3.美国国立卫生研究院（NIH）项目“开发和临床验证面向任务的图像质量评估的领域感知型拟人模型观察者”（R01EB036082），参与。

学术成果

一、主要论文：

1.X. Zhang, Y. Yang, P. H. Pretorius, P. J. Slomka, and M. A. King, “Cardiac motion correction with a deep learning network for perfusion defect assessment in single-photon emission computed tomography myocardial perfusion imaging,” Journal of Nuclear Cardiology, 2025.

2.X. Zhang, Y. Yang, P. H. Pretorius, and M. A. King, “Assessment of Deep-Learning Based Motion Compensation on Detection of Perfusion Defects in Cardiac-Gated SPECT Images,” IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023

3.X. Zhang, Á. Belloso, Y. Yang, M. N. Wernick, P. Hendrik Pretorius, and M. A. King, “A Study of Deep Learning Networks for Motion Compensation in Cardiac Gated Spect Images”, IEEE International Conference on Image Processing (ICIP), 2022

4.X. Zhang, Y. Yang, J. G. Brankov, P. H. Pretorius, and M. A. King, “A Feasibility Study on Deep Learning Denoising for Standard-Dose Cardiac-Gated SPECT Images”, IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and International Symposium on Room-Temperature Semiconductor Detectors (RTSD), 2023

5.X. Zhang, Y. Yang, P. H. Pretorius, and M. A. King, “Exploring Anatomical Similarity in Cardiac-Gated Spect Images for A Deep Learning Network,” IEEE International Conference on Image Processing (ICIP), 2023.

6.Á. Belloso, X. Zhang, Y. Yang, M. N. Wernick, P. Hendrik Pretorius, and M. A. King, “A Feasibility Study of Motion Compensation for Cardiac Gated Spect Images Using a Cascaded Network”, IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022.

7.X. Zhang, Y. Yang, J. G. Brankov, P. H. Pretorius, and M. A. King, “Temporal Regularization for Robust Motion Compensation in Reduced Dose Cardiac-Gated Spect Images,” IEEE International Conference on Image Processing (ICIP), 2024.

8.X. Zhang, Y. Yang, J. G. Brankov, M. N. Wernick, P. H. Pretorius, and M. A. King, “A Feasibility Study of Increasing Temporal Resolution in Cardiac-gated SPECT Acquisitions”, IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), 2024.

9.X. Zhang, Y. Yang, J. G. Brankov, P. Hendrik Pretorius, and M. A. King, “Improving Temporal Resolution in Clinical Cardiac-gated SPECT Studies via Surrogate Training in Deep Learning Denoising”, IEEE International Symposium on Biomedical Imaging (ISBI), 2024.

10. X. Zhang, Y. Yang, J. G. Brankov, P. Hendrik Pretorius, and M. A. King, “Training Strategies for Increased Temporal Resolution in Clinical Cardiac-Gated SPECT Studies With Deep Learning Denoising”, IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 2025.

11. X. Zhang, Y. Yang, J. G. Brankov and M. A. King, "A Noise-to-Noise Training Approach for Robust Motion-Compensated Processing in Cardiac-Gated Images," IEEE International Conference on Image Processing (ICIP), 2025.

12. X. Zhang, Y. Yang, J. G. Brankov and M. A. King, "Toward Achieving Adjustable Smoothing Level in Cardiac-Gated SPECT Studies with a Deep Learning Denoising Network," IEEE 23rd International Symposium on Biomedical Imaging (ISBI), 2026.

奖励和荣誉

1.湖南省芙蓉计划青年人才（科技创新类, 2026）

2.《Journal of Nuclear Cardiology》Best Translational Science Paper Award（Technical/AI Category，2026）