Tiantian Li

Title: The Innovative Contributions of Tiantian Li

Introduction

Tiantian Li is a notable inventor based in Oakland, CA, who has made significant contributions to the field of image processing and nuclear medicine. With a total of 5 patents, his work focuses on advanced methods for image denoising and scatter estimation.

Latest Patents

One of Tiantian Li's latest patents is titled "Apparatus and methods for unsupervised image denoising using double over-parameterization." This invention involves a method, apparatus, and non-transitory computer-readable storage medium for image denoising. It utilizes a deep image prior (DIP) neural network trained to produce a denoised image by inputting a second medical image and combining converging noise with the output of the DIP network. The goal is to approximate the first medical image at the end of the training, resulting in a high-quality denoised image.

Another significant patent is "Scatter estimation for PET from image-based convolutional neural network." This invention provides a method, system, and computer-readable medium for performing nuclear medicine scatter correction estimation, sinogram estimation, and image reconstruction. It employs deep convolutional neural networks (DCNN) to estimate scatter sinograms directly from emission and attenuation correction data, enhancing the accuracy of nuclear medicine imaging.

Career Highlights

Tiantian Li has worked with prestigious organizations, including the University of California and Canon Medical Systems Corporation. His experience in these institutions has allowed him to develop and refine his innovative techniques in image processing and medical imaging.

Collaborations

Throughout his career, Tiantian has collaborated with talented individuals such as Zhaoheng Xie and Wenyuan Qi, who have contributed to his research and development efforts.

Conclusion

Tiantian Li's innovative work in image denoising and nuclear medicine has positioned him as a key figure in his field. His patents reflect a commitment to advancing technology and improving medical imaging techniques.