A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task
This work addresses medical image captioning for radiology, but it is incremental as it applies a standard deep neural network approach without novel methods or external data.
The authors tackled the problem of automatically labeling radiology images with medical concepts for the ImageCLEFmed Caption 2020 task, achieving an F1 score of 0.375 and ranking 12th among submitted systems.
The aim of ImageCLEFmed Caption task is to develop a system that automatically labels radiology images with relevant medical concepts. We describe our Deep Neural Network (DNN) based approach for tackling this problem. On the challenge test set of 3,534 radiology images, our system achieves an F1 score of 0.375 and ranks high, 12th among all systems that were successfully submitted to the challenge, whereby we only rely on the provided data sources and do not use any external medical knowledge or ontologies, or pretrained models from other medical image repositories or application domains.