2 citations · 4 across the 4 of their papers we have counts for
4 papers
Expert-Level Annotation Quality Achieved by Gamified Crowdsourcing for B-line Segmentation in Lung Ultrasound
Mike Jin, Nicole M Duggan, Varoon Bashyakarla +7
Accurate and scalable annotation of medical data is critical for the development of medical AI, but obtaining time for annotation from medical experts is challenging. Gamified crow…
Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Dataset Labeling
Nicole M Duggan, Mike Jin, Maria Alejandra Duran Mendicuti +10
Study Objective: Machine learning models have advanced medical image processing and can yield faster, more accurate diagnoses. Despite a wealth of available medical imaging data, h…
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound
Ruben T. Lucassen, Mohammad H. Jafari, Nicole M. Duggan +18
Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key fi…
Learning Topological Interactions for Multi-Class Medical Image Segmentation
Saumya Gupta, Xiaoling Hu, James Kaan +10
Deep learning methods have achieved impressive performance for multi-class medical image segmentation. However, they are limited in their ability to encode topological interactions…