Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision

1 code implementation • 28 Oct 2023 • Bobby Azad, Reza Azad, Sania Eskandari, Afshin Bozorgpour, Amirhossein Kazerouni, Islem Rekik, Dorit Merhof

Foundation models, large-scale, pre-trained deep-learning models adapted to a wide range of downstream tasks have gained significant interest lately in various deep-learning problems undergoing a paradigm shift with the rise of these models.

Skin Lesion Segmentation Improved by Transformer-based Networks with Inter-scale Dependency Modeling

1 code implementation • 20 Oct 2023 • Sania Eskandari, Janet Lumpp, Luis Sanchez Giraldo

As a result, we propose a U-shaped hierarchical Transformer-based structure for skin lesion segmentation and an Inter-scale Context Fusion (ISCF) method that uses attention correlations in each stage of the encoder to adaptively combine the contexts from each stage to mitigate semantic gaps.

Decoder Image Segmentation +4

Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks

no code implementations • 20 Oct 2023 • Sania Eskandari, Janet Lumpp

Melanoma is a dangerous form of skin cancer caused by the abnormal growth of skin cells.

Decoder Image Segmentation +4