Výsledky vyhledávání - "FAYAD, ZAHI A."

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

Autor: Liu, Zelong, Tieu, Andrew, Patel, Nikhil, Zhou, Alexander, Soultanidis, George, Fayad, Zahi A., Deyer, Timothy, Mei, Xueyan

Artificial Intelligence (AI) has the potential to revolutionize diagnosis and segmentation in medical imaging. However, development and clinical implementation face multiple challenges including limited data availability, lack of generalizability, an

Externí odkaz: http://arxiv.org/abs/2402.01034

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

Autor: Zhou, Alexander, Liu, Zelong, Tieu, Andrew, Patel, Nikhil, Sun, Sean, Yang, Anthony, Choi, Peter, Fauveau, Valentin, Soultanidis, George, Huang, Mingqian, Doshi, Amish, Fayad, Zahi A., Deyer, Timothy, Mei, Xueyan

Purpose To develop a deep learning model for multi-anatomy and many-class segmentation of diverse anatomic structures on MRI imaging. Materials and Methods In this retrospective study, two datasets were curated and annotated for model development and

Externí odkaz: http://arxiv.org/abs/2402.01031

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

Autor: Liu, Zelong, Zhou, Alexander, Yang, Arnold, Yilmaz, Alara, Yoo, Maxwell, Sullivan, Mikey, Zhang, Catherine, Grant, James, Li, Daiqing, Fayad, Zahi A., Huver, Sean, Deyer, Timothy, Mei, Xueyan

Deep learning in medical imaging often requires large-scale, high-quality data or initiation with suitably pre-trained weights. However, medical datasets are limited by data availability, domain-specific knowledge, and privacy concerns, and the creat

Externí odkaz: http://arxiv.org/abs/2312.05953

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