3 citations · 3 across the 4 of their papers we have counts for
4 papers
A Simple Framework Uniting Visual In-context Learning with Masked Image Modeling to Improve Ultrasound Segmentation
Yuyue Zhou, Banafshe Felfeliyan, Shrimanti Ghosh +6
Conventional deep learning models deal with images one-by-one, requiring costly and time-consuming expert labeling in the field of medical imaging, and domain-specific restriction…
Application Of Vision-Language Models For Assessing Osteoarthritis Disease Severity
Banafshe Felfeliyan, Yuyue Zhou, Shrimanti Ghosh +4
Osteoarthritis (OA) poses a global health challenge, demanding precise diagnostic methods. Current radiographic assessments are time consuming and prone to variability, prompting t…
Self-supervised TransUNet for Ultrasound regional segmentation of the distal radius in children
Yuyue Zhou, Jessica Knight, Banafshe Felfeliyan +3
Supervised deep learning offers great promise to automate analysis of medical images from segmentation to diagnosis. However, their performance highly relies on the quality and qua…
Self-Supervised-RCNN for Medical Image Segmentation with Limited Data Annotation
Banafshe Felfeliyan, Abhilash Hareendranathan, Gregor Kuntze +4
Many successful methods developed for medical image analysis that are based on machine learning use supervised learning approaches, which often require large datasets annotated by…