Efficient Scopeformer: Toward Scalable and Rich Feature Extraction for Intracranial Hemorrhage Detection

Efficient Scopeformer: Toward Scalable and Rich Feature Extraction for Intracranial Hemorrhage Detection

The quality and richness of feature maps extracted by convolution neural networks (CNNs) and vision Transformers (ViTs) directly relate to the robust model performance. In medical computer vision, these information-rich features are crucial for detecting rare cases within large datasets. This work p...

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Bibliographic Details
Main Authors: Yassine Barhoumi, Nidhal Carla Bouaynaya, Ghulam Rasool
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Computed tomography (CT)
intracranial hemorrhage
medical imaging
convolutional neural networks
vision transformers
feature maps
Online Access:https://ieeexplore.ieee.org/document/10201867/

Internet

https://ieeexplore.ieee.org/document/10201867/

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