Location History:
- Dalian, CN (2021)
- Liaoning, CN (2021 - 2023)
Company Filing History:
Years Active: 2021-2023
Title: Innovations in Lung Texture Recognition by Xinchen Ye
Introduction
Xinchen Ye is a prominent inventor based in Liaoning, China, known for his significant contributions to the field of image processing and computer vision. With a total of six patents to his name, he has developed innovative methods that enhance the recognition of lung textures in computed tomography (CT) images.
Latest Patents
One of his latest patents is the "Deep network lung texture recognition method combined with multi-scale attention." This invention focuses on accurately recognizing the typical texture of diffuse lung disease in CT images. By designing a unique attention mechanism module and a multi-scale feature fusion module, Xinchen has constructed a deep convolutional neural network that achieves high-precision automatic recognition of these textures. The proposed network structure is not only clear but also easy to construct and implement.
Another notable patent is the "Unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition." This method allows a deep network model trained on one type of CT data to be effectively applied to another CT image without the need for manual labeling. Utilizing an adversarial learning mechanism and a specially designed content consistency network module, this approach fine-tunes the deep network model to maintain high performance in lung texture recognition. This innovation saves development labor and time costs while being easy to implement and highly practical.
Career Highlights
Xinchen Ye is affiliated with Dalian University of Technology, where he continues to advance research in his field. His work has garnered attention for its practical applications in medical imaging and diagnostics.
Collaborations
Xinchen collaborates with notable colleagues, including Haojie Li and Lin Lin, who contribute to his research endeavors.
Conclusion
Xinchen Ye's innovative patents in lung texture recognition demonstrate his commitment to advancing medical imaging technology. His contributions are paving the way for more efficient and accurate diagnostic methods in healthcare.