Chengdu, China

Yulin Ji


Average Co-Inventor Count = 5.3

ph-index = 2

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2018-2019

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3 patents (USPTO):Explore Patents

Title: Innovations of Yulin Ji in Medical Imaging

Introduction

Yulin Ji is a prominent inventor based in Chengdu, China, known for his significant contributions to the field of medical imaging. With a total of three patents to his name, he has developed innovative methods that enhance the quality of X-ray images, particularly in chest radiography.

Latest Patents

One of Yulin Ji's latest patents is a method for rib suppression in X-ray chest images based on a Poisson model. This method employs contourlet transformation to enhance the texture of the image while effectively suppressing the ribs without the need for precise segmentation. By utilizing the correlation of transformation coefficients across different scales, the method improves the observation quality of X-ray images. Another notable patent is a lung lobe contour extraction method aimed at digital radiography (DR). This method involves obtaining a representative lung lobe contour template through offline training and utilizing a series of image processing techniques, including Gabor filter banks and Zhan-Suen refinement algorithms, to accurately extract lung lobe contours from chest DR images.

Career Highlights

Yulin Ji is affiliated with Sichuan University, where he continues to advance research in medical imaging technologies. His work has garnered attention for its practical applications in improving diagnostic imaging techniques, which are crucial for patient care.

Collaborations

Yulin Ji collaborates with notable colleagues, including Junfeng Wang and Zongan Liang, who contribute to his research endeavors and innovations in the field.

Conclusion

Yulin Ji's innovative approaches to medical imaging, particularly in rib suppression and lung lobe contour extraction, demonstrate his commitment to enhancing diagnostic techniques. His contributions are vital for improving the accuracy and effectiveness of medical imaging in clinical settings.

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