VISION-MAE: A Foundation Model for Medical Image Segmentation and Classification

no code implementations • 1 Feb 2024 • Zelong Liu, Andrew Tieu, Nikhil Patel, Alexander Zhou, George Soultanidis, Zahi A. Fayad, Timothy Deyer, Xueyan Mei

A foundation model, which is a large-scale pre-trained AI model, offers a versatile base that can be adapted to a variety of specific tasks and contexts.

Image Segmentation Medical Image Segmentation +3

MRAnnotator: A Multi-Anatomy Deep Learning Model for MRI Segmentation

no code implementations • 1 Feb 2024 • Alexander Zhou, Zelong Liu, Andrew Tieu, Nikhil Patel, Sean Sun, Anthony Yang, Peter Choi, Valentin Fauveau, George Soultanidis, Mingqian Huang, Amish Doshi, Zahi A. Fayad, Timothy Deyer, Xueyan Mei

The external dataset was used to evaluate nnU-Net model generalizability and performance in all classes on independent imaging data.

Anatomy MRI segmentation +1

RadImageGAN -- A Multi-modal Dataset-Scale Generative AI for Medical Imaging

no code implementations • 10 Dec 2023 • Zelong Liu, Alexander Zhou, Arnold Yang, Alara Yilmaz, Maxwell Yoo, Mikey Sullivan, Catherine Zhang, James Grant, Daiqing Li, Zahi A. Fayad, Sean Huver, Timothy Deyer, Xueyan Mei

We showed that using synthetic auto-labeled data from RadImageGAN can significantly improve performance on four diverse downstream segmentation datasets by augmenting real training data and/or developing pre-trained weights for fine-tuning.

Segmentation