8 citations · 20 across the 8 of their papers we have counts for
9 papers
An Interactive Interpretability System for Breast Cancer Screening with Deep Learning
Yuzhe Lu, Adam Perer
Deep learning methods, in particular convolutional neural networks, have emerged as a powerful tool in medical image computing tasks. While these complex models provide excellent p…
Holistic Fine-grained GGS Characterization: From Detection to Unbalanced Classification
Yuzhe Lu, Haichun Yang, Zuhayr Asad +5
Recent studies have demonstrated the diagnostic and prognostic values of global glomerulosclerosis (GGS) in IgA nephropathy, aging, and end-stage renal disease. However, the fine-g…
Compressive Neural Representations of Volumetric Scalar Fields
Yuzhe Lu, Kairong Jiang, Joshua A. Levine +1
We present an approach for compressing volumetric scalar fields using implicit neural representations. Our approach represents a scalar field as a learned function, wherein a neura…
SimTriplet: Simple Triplet Representation Learning with a Single GPU
Quan Liu, Peter C. Louis, Yuzhe Lu +9
Contrastive learning is a key technique of modern self-supervised learning. The broader accessibility of earlier approaches is hindered by the need of heavy computational resources…
Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis
Yuzhe Lu, Aadarsh Jha, Yuankai Huo
Annotated medical images are typically rarer than labeled natural images since they are limited by domain knowledge and privacy constraints. Recent advances in transfer and contras…
Improve Global Glomerulosclerosis Classification with Imbalanced Data using CircleMix Augmentation
Yuzhe Lu, Haichun Yang, Zheyu Zhu +3
The classification of glomerular lesions is a routine and essential task in renal pathology. Recently, machine learning approaches, especially deep learning algorithms, have been u…