Mr. Zhenghong Yu | Medical Imaging | Best Researcher Award
Professor | Henan Provincial People’s Hospital | China
Yu Zhenghong is a distinguished orthopedic surgeon and academic based in Zhengzhou, China, currently serving at the Department of Surgery of Spine and Spinal Cord, Henan Provincial People’s Hospital, and the People’s Hospital of Zhengzhou University. With an extensive background in orthopedics and spinal surgery, his expertise bridges traditional Chinese medicine and modern clinical anatomy. Dr. Yu obtained his Bachelor’s degree in Orthopedics and Traumatology from Beijing University of Chinese Medicine, followed by a Master’s degree in Traditional Chinese Medicine from Henan University of Chinese Medicine, and later a Ph.D. in Clinical Applied Anatomy from Southern Medical University. His research encompasses the pathogenesis, diagnosis, and surgical treatment of complex spinal disorders, with particular focus on spinal deformity correction, spinal cord injury management, and minimally invasive spinal techniques. He has contributed significantly to understanding vertebral biomechanics, surgical navigation systems, and tissue regeneration strategies for spinal repair. His clinical excellence combines traditional Chinese orthopedic methods with advanced surgical technologies, enhancing patient recovery outcomes and reducing postoperative complications. As a chief physician and educator, he has mentored numerous graduate and postgraduate students, guiding them in clinical orthopedics and translational spine research. His work has been published in several national and international journals, highlighting innovative approaches in spinal fixation, intervertebral disc degeneration treatment, and spinal cord protective mechanisms. Dr. Yu Zhenghong’s commitment to research excellence and his integration of Eastern and Western medical principles position him as a leading figure in spinal surgery and orthopedic innovation.
Featured Publications:
Yu, Z., Cao, Z., Wu, X., Bai, X., Qin, Y., Zhuo, W., Xiao, Y., Zhang, X., & Xue, H. (n.d.). Automatic image-based detection technology for two critical growth stages of maize: Emergence and three-leaf stage. Agricultural and Forest Meteorology, 174, 65–84. https://doi.org/10.1016/j.agrformet.2013.02.014
Bai, X. D., Cao, Z. G., Wang, Y., Yu, Z. H., Zhang, X. F., & Li, C. N. (n.d.). Crop segmentation from images by morphology modeling in the CIE L a* b* color space.* Computers and Electronics in Agriculture, 99, 21–34. https://doi.org/10.1016/j.compag.2013.08.021
Bai, X., Cao, Z., Wang, Y., Yu, Z., Hu, Z., Zhang, X., & Li, C. (n.d.). Vegetation segmentation robust to illumination variations based on clustering and morphology modelling. Biosystems Engineering, 125, 80–97. https://doi.org/10.1016/j.biosystemseng.2014.07.003
Ye, M., Cao, Z., Yu, Z., & Bai, X. (n.d.). Crop feature extraction from images with probabilistic superpixel Markov random field. Computers and Electronics in Agriculture, 114, 247–260. https://doi.org/10.1016/j.compag.2015.04.009
Yu, Z., Lu, D., Ye, J., & Wang, Y. (n.d.). Plant detection and counting: Enhancing precision agriculture in UAV and general scenes. IEEE Access, 11(1), 116196–116205. https://doi.org/10.1109/ACCESS.2023.3301234
Yu, Z., Ye, J., Li, C., Zhou, H., & Li, X. (n.d.). TasselLFANet: A novel lightweight multi-branch feature aggregation neural network for high-throughput image-based maize tassels detection and counting. Frontiers in Plant Science, 14, 1291. https://doi.org/10.3389/fpls.2023.1129123
Ye, M., Cao, Z., & Yu, Z. (n.d.). An image-based approach for automatic detecting tasseling stage of maize using spatio-temporal saliency. MIPPR: Remote Sensing Image Processing, Geographic Information Systems and Other Applications.