6 citations · 19 across the 12 of their papers we have counts for
14 papers
Graph-Ensemble Learning Model for Multi-label Skin Lesion Classification using Dermoscopy and Clinical Images
Peng Tang, Yang Nan, Tobias Lasser
Many skin lesion analysis (SLA) methods recently focused on developing a multi-modal-based multi-label classification method due to two factors. The first is multi-modal data, i.e.…
The Beauty or the Beast: Which Aspect of Synthetic Medical Images Deserves Our Focus?
Xiaodan Xing, Yang Nan, Federico Felder +2
Training medical AI algorithms requires large volumes of accurately labeled datasets, which are difficult to obtain in the real world. Synthetic images generated from deep generati…
You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images
Xiaodan Xing, Federico Felder, Yang Nan +3
Synthetic images generated from deep generative models have the potential to address data scarcity and data privacy issues. The selection of synthesis models is mostly based on ima…
Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation
Yang Nan, Javier Del Ser, Zeyu Tang +7
Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming a…
Region-Based Evidential Deep Learning to Quantify Uncertainty and Improve Robustness of Brain Tumor Segmentation
Hao Li, Yang Nan, Javier Del Ser +1
Despite recent advances in the accuracy of brain tumor segmentation, the results still suffer from low reliability and robustness. Uncertainty estimation is an efficient solution t…
Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network
Yang Nan, Peng Tang, Guyue Zhang +5
Tissue segmentation is the mainstay of pathological examination, whereas the manual delineation is unduly burdensome. To assist this time-consuming and subjective manual step, rese…