Michael Tin-Cheung Ying

Title: Michael Tin-Cheung Ying: Innovator in Ultrasound Image Segmentation

Introduction

Michael Tin-Cheung Ying is a notable inventor based in Hong Kong, CN. He has made significant contributions to the field of medical imaging, particularly in the optimization of ultrasound image segmentation. His innovative approach has the potential to enhance the accuracy of identifying tissue objects within ultrasound images.

Latest Patents

Michael Tin-Cheung Ying holds a patent for a method titled "Segmenting ultrasound images." This invention provides optimizations for segmenting tissue objects included in an ultrasound image. Initially, raw pixel data is received, where each pixel corresponds to ultrasound information. This raw pixel data is processed through a first fully convolutional network to generate a first segmentation label map, which includes a first set of objects segmented into a coarse segmentation class. The first map is then processed through a second fully convolutional network to generate a second segmentation label map, which is refined using the raw pixel data as a base reference. This second map includes a second set of objects segmented into a fine segmentation class. A contour optimization algorithm is applied to at least one of the second set of objects to refine that object's contour boundary, ultimately identifying it as corresponding to a lymph node. He has 1 patent in this area.

Career Highlights

Throughout his career, Michael has worked with prestigious institutions such as the University of Notre Dame Du Lac and The Hong Kong Polytechnic University. His work has been instrumental in advancing the field of ultrasound imaging and improving diagnostic techniques.

Collaborations

Michael has collaborated with talented individuals in his field, including Lin Yang and Danny Ziyi Chen. Their combined expertise has contributed to the success of his innovative projects.

Conclusion

Michael Tin-Cheung Ying is a prominent figure in the realm of ultrasound image segmentation, with a focus on enhancing the accuracy of medical imaging. His contributions are paving the way for advancements in diagnostic technology.