6 citations · 16 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…
Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers
Jiahao Huang, Yingying Fang, Yang Nan +9
Research studies have shown no qualms about using data driven deep learning models for downstream tasks in medical image analysis, e.g., anatomy segmentation and lesion detection,…
Automatic Fine-grained Glomerular Lesion Recognition in Kidney Pathology
Yang Nan, Fengyi Li, Peng Tang +5
Recognition of glomeruli lesions is the key for diagnosis and treatment planning in kidney pathology; however, the coexisting glomerular structures such as mesangial regions exacer…
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge
Nicholas Heller, Fabian Isensee, Klaus H. Maier-Hein +38
There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors a…