This inventor holds 1 USPTO granted patent. Top assignee: Zhejiang University. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Deli Wang: Innovator in Image and Segmentation Label Generative Models
Introduction
Deli Wang is a prominent inventor based in Hangzhou, China. He has made significant contributions to the field of image processing and segmentation through his innovative patent. His work focuses on developing models that enhance the quality and efficiency of image data generation.
Latest Patents
Deli Wang holds a patent titled "Image and segmentation label generative model for tree-structured data and application." This patent presents a model that includes a simulation model for tree-structured images, designed using a small amount of expert knowledge. The generative network model is based on a morphological loss function. This technology can generate simulated tree-structured images with labels that closely resemble real target images. It is particularly useful in generating image and segmentation labels for various medical images, including brain neurons, retinal vessels, and trachea in the lungs. The data quality achieved can reach the level of manually annotated data. This model is notable for being the first to automatically generate segmentation-level data, offering advantages such as simple and flexible model configuration, high-quality generated data, and a wide range of applications.
Career Highlights
Deli Wang is affiliated with Zhejiang University, where he continues to advance his research and development in image processing technologies. His work has garnered attention for its innovative approach and practical applications in the medical field.
Collaborations
Deli Wang has collaborated with notable colleagues, including Nenggan Zheng and Chao Liu. Their combined expertise contributes to the advancement of research in image segmentation and generative modeling.
Conclusion
Deli Wang's contributions to the field of image processing through his innovative patent demonstrate his commitment to advancing technology in medical imaging. His work not only enhances the quality of data generation but also opens new avenues for research and application in various medical fields.