Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs

Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs

Radiographs are a versatile diagnostic tool for the detection and assessment of pathologies, for treatment planning or for navigation and localization purposes in clinical interventions. However, their interpretation and assessment by radiologists can be tedious and error-prone. Thus, a wide variety...

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Bibliographic Details
Main Authors: Behrendt Finn, Bhattacharya Debayan, Krüger Julia, Opfer Roland, Schlaefer Alexander
Format: Article
Language:English
Published: De Gruyter 2022-07-01
Series:Current Directions in Biomedical Engineering
Subjects:
deep learning
chest radiograph
vision transformer
convolutional neural network
chexpert
Online Access:https://doi.org/10.1515/cdbme-2022-0009

Internet

https://doi.org/10.1515/cdbme-2022-0009

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