Yu-Bing Chang

Title: Innovations of Yu-Bing Chang

Introduction

Yu-Bing Chang is an accomplished inventor based in Albany, NY (US). He holds a total of 4 patents that showcase his contributions to the field of imaging technology. His work primarily focuses on enhancing imaging systems through innovative methods and algorithms.

Latest Patents

One of his latest patents is titled "Apparatus, method, and non-transitory computer-readable storage medium for generating a task-aware dynamic sparse-view scanning procedure." This patent describes a system and method for controlling an acquisition system to obtain a next set of projection data based on a currently acquired set. The method utilizes learned imaging conditions derived from training data, which includes projection data and dose information. In one embodiment, the initial dose and angle for obtaining the initial set of projection data are chosen at random, while in another, they are based on a test scan and a trained neural network.

Another significant patent is "X-ray imaging restoration using deep learning algorithms." This patent outlines a general workflow for deep learning-based image restoration in X-ray and fluoroscopy. It involves generating higher quality and lower quality images as training data, which can be categorized by anatomical structure. The trained model can be employed for real-time inferencing, with improvements achieved through various techniques, including model pruning and precision reduction.

Career Highlights

Yu-Bing Chang has worked with notable organizations such as Canon Medical Systems Corporation and the University of Chicago. His experience in these institutions has contributed to his expertise in imaging technologies and deep learning applications.

Collaborations

He has collaborated with professionals like Joseph Manak and Xiaochuan Pan, further enhancing his research and development efforts in the field.

Conclusion

Yu-Bing Chang's innovative patents and career achievements reflect his significant contributions to imaging technology. His work continues to influence advancements in the field, showcasing the importance of innovation in medical imaging.