Shuai Jiang (Svy.J)

I am currently a Ph.D. student major in Control Science and Engineering at Hunan University, working under the supervision of Prof. Dr. Min Liu. My research interests include industrial imaging and defect detection, weakly supervised learning and medical image anylasis. Before entering Hunan University, I received my M.S. and B.S. degree from Xiangtan University in 2023 and 2020. (Contact me: svyj@hnu.edu.cn)

News of paper acceptance and awards

  • [Apr. 2024] One paper on “weakly supervised surface defect localization” was submitted to IEEE Transactions on Automation Science and Engineering [Code]
  • [Apr. 2023] I was awarded the 28th “Graduate President Scholarship” at Xiangtan University
  • [Mar. 2023] I was awarded the title of “Outstanding Graduate Student” of Hunan Provincial Ordinary Higher Education Institutions
  • [Mar. 2023] I was awarded the title of “Outstanding Graduate Student” of Xiangtan University
  • [Jan. 2023] One paper on “retinal layer segmentation in OCT” was accepted by the Journal of Software (软件学报) (CCF-A Chinese journal) [Paper]
  • [Oct. 2022] I was awarded the “Special Academic Scholarship” again with rank of 1/70
  • [Sept. 2022] I was awarded the “Graduate National Scholarship”
  • [Jul. 2022] One paper on “biomarkers segmentation in OCTA” was accepted by IEEE Transactions on Instrumentation and Measurement [Paper] [Code]
  • [Oct. 2021] I was awarded the “Xinhualian Group Education Scholarship”
  • [Oct. 2021] I was awarded the “Special Academic Scholarship” with rank of 1/70
  • [Dec. 2020] I won the third prize in the 4th International Symposium on Image Computing and Digital Medicine (ISICDM) in “Lung Tissue Segmentation Challenge” [ISICDM 2023]
  • [Oct. 2020] I was awarded the “First Class Academic Scholarship” with rank of 1/70

Publications

Kai Hu, Shuai Jiang, Yuan Zhang, Xuanya Li, and Xieping Gao, “Joint-seg: Treat foveal avascular zone and retinal vessel segmentation in octa images as a joint task,” IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1–13, 2022. [Paper] [Code]

胡凯, 蒋帅, 刘冬, 高协平. 基于端到端深度神经网络和图搜索的OCT图像视网膜层边界分割方法. 软件学报, 2023. [Paper]

Featured Works (Detailed Introduction in Chinese)

  1. OCTA图像中生物标志物的联合分割方法研究
  • 项目来源：国家自然科学基金（61972333），湖南省教育厅优秀青年基金（21B0172，19A496）
  • 项目描述：针对 OCTA 图像中生物标志物分割过程中，所存在的约束建模缺乏问题，设计联合分割方法以建模生物标志物之间的空间约束关系，并同时分割两个生物标志物
  • 主要内容：联合分割框架和针对各生物标志物的模型框架设计，利用 Python 语言和 Pytorch 深度学习框架开发图像分割算法，并撰写英文科技论文
  • 项目结果：设计了有效的联合分割模型 Joint-Seg，极大地提高了 OCTA 图像中 FAZ 和 RV 分割的效率和精度
  • 成果发表：K. Hu, S. Jiang, Y. Zhang, X. Li and X. Gao, “Joint-Seg: Treat Foveal Avascular Zone and Retinal Vessel Segmentation in OCTA Images as a Joint Task,” in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-13, 2022, Art no. 4007113, doi: 10.1109/TIM.2022.3193188. [Paper] [Code]
  1. OCT图像中的视网膜层边界分割方法研究
  • 项目来源：国家自然科学基金（61972333），湖南省教育厅优秀青年基金（21B0172，19A496）
  • 项目描述：由于视网膜层变形和边界对比度低的问题，视网膜层边界的精确分割已成为医学图像处理领域的挑战性问题之一，现有分割方法缺乏对上下文信息、重要边界信息等关键边界相关信息的考虑而导致边界不完整、不连续的问题
  • 主要内容：设计充分提取视网膜边界全局上下文信息的深度神经网络，并将其与图搜索算法结合，利用 Python 语言和 Pytorch 深度学习框架开发图像分割算法，并撰写中文科技论文
  • 项目结果：提出了一种基于端到端深度神经网络和图搜索的 OCT 图像视网膜层粗到细边界分割方法，解决了非端到端方法中普遍存在的“断层”现象，在多个公开数据集上达到了 SOTA 效果
  • 成果发表：胡凯,蒋帅,刘冬等.基于端到端深度神经网络和图搜索的OCT图像视网膜层边界分割方法[J/OL].软件学报:1-16[2023-07-07].DOI:10.13328/j.cnki.jos.006895. [Paper]