A Simple Framework Uniting Visual In-context Learning with Masked Image Modeling to Improve Ultrasound Segmentation

1 code implementation • 22 Feb 2024 • Yuyue Zhou, Banafshe Felfeliyan, Shrimanti Ghosh, Jessica Knight, Fatima Alves-Pereira, Christopher Keen, Jessica Küpper, Abhilash Rakkunedeth Hareendranathan, Jacob L. Jaremko

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 limits model generalizability.

In-Context Learning Segmentation +1

Self-supervised TransUNet for Ultrasound regional segmentation of the distal radius in children

no code implementations • 18 Sep 2023 • Yuyue Zhou, Jessica Knight, Banafshe Felfeliyan, Christopher Keen, Abhilash Rakkunedeth Hareendranathan, Jacob L. Jaremko

However, their performance highly relies on the quality and quantity of the data annotation.

Self-Supervised Learning

Physics Driven Domain Specific Transporter Framework with Attention Mechanism for Ultrasound Imaging

1 code implementation • 13 Sep 2021 • Arpan Tripathi, Abhilash Rakkunedeth, Mahesh Raveendranatha Panicker, Jack Zhang, Naveenjyote Boora, Jessica Knight, Jacob Jaremko, Yale Tung Chen, Kiran Vishnu Narayan, Kesavadas C

Also, on employing for classification of the given lung image into normal and abnormal classes, the proposed approach, even with no prior training, achieved an average accuracy of 97\% and an average F1-score of 95\% respectively on the task of co-classification with 3 fold cross-validation.