- UCLA Bioengineering
Office: 924 Westwood Blvd, Suite 420, Room Q
I received my B.S. in Electrical Engineering at Fudan University in 2015. During that time, I worked as an undergraduate researcher on graph models and its' applications in Traditional Chinese Medicine at Adaptive Network and Control Lab. My current research focuses on using weakly- or semi-supervised models to learn representations from large-scale whole slide image datasets, and combine histopathological features, imaging representation and clinical variable for disease progression prediction.
- Li W, Li J, Sarma KV, Ho KC, Shen S, Knudsen BS, Gertych A, Arnold CW. Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images. IEEE transactions on medical imaging [Internet]. IEEE; 2018;8(1):14429. Retrieved from: https://ieeexplore.ieee.org/abstract/document/8490855 DOI: 10.1109/TMI.2018.2875868. PDF
- Ing N, Ma Z, Li J, Salemi H, Arnold C, Knudsen BS, Gertych A. Semantic segmentation for prostate cancer grading by convolutional neural networks. Medical Imaging 2018: Digital Pathology. International Society for Optics and Photonics; 2018. p. 105811B.
- Li J, Speier W, Ho KC, Sarma KV, Gertych A, Knudsen BS, Arnold CW. An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies. Computerized Medical Imaging and Graphics. Elsevier; 2018;69:125–133.
- Li J, Sarma KV, Ho KC, Gertych A, Knudsen BS, Arnold CW. A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies. AMIA Annual Symposium Proceedings. American Medical Informatics Association; 2017. p. 1140.