Zixiao Li

Title: Innovations of Zixiao Li in Medical Imaging

Introduction

Zixiao Li is a prominent inventor based in Beijing, China, known for his contributions to the field of medical imaging. He has been awarded two patents that showcase his innovative approaches to understanding and processing brain-related conditions. His work is significant in advancing the methodologies used in medical diagnostics.

Latest Patents

Zixiao Li's latest patents include a "Method and system for extracting multi-dimensional disconnection network region of symptom mapping." This invention involves registering a lesion image to a brain standard space and obtaining diffusion magnetic resonance images and resting-state functional magnetic resonance images of healthy control groups. The method constructs a structural disconnection weighting network corresponding to lesions and determines the multi-dimensional disconnection network region of the lesions for effective symptom mapping.

Another notable patent is the "Method and system for processing intracranial large vessel image, electronic device, and medium." This invention focuses on acquiring original intracranial large vessel images and applying a cerebrovascular segmentation model to obtain cerebrovascular mask images. It includes training a convolutional neural network model to classify cerebrovascular occlusions, which enhances the identification of target regions in medical images.

Career Highlights

Zixiao Li has worked with several esteemed institutions, including Beijing Tiantan Hospital, Capital Medical University, and Beihang University. His experience in these organizations has allowed him to collaborate with leading professionals in the field of medical research and imaging.

Collaborations

Zixiao Li has collaborated with notable coworkers such as Yongjun Wang and Tao Liu. Their joint efforts have contributed to the advancements in medical imaging technologies and methodologies.

Conclusion

Zixiao Li's innovative patents and career achievements reflect his dedication to improving medical imaging techniques. His work continues to influence the field and offers promising advancements for future medical diagnostics.