@inproceedings{a1c2ae847f6c4fadb422d0dcaea25080,
title = "Pristine Annotations-Based Multi-modal Trained Artificial Intelligence Solution to Triage Chest X-Ray for COVID-19",
abstract = "The COVID-19 pandemic continues to spread and impact the well-being of the global population. The front-line imaging modalities computed tomography (CT) and X-ray play an important role for triaging COVID-19 patients. Considering the limited access to resources (both hardware and trained personnel) and decontamination, CT may not be ideal for triaging suspected subjects. Artificial intelligence (AI) assisted X-ray based applications for triaging and monitoring COVID-19 patients in a timely manner with the additional ability to delineate the disease region boundary are seen as a promising solution. Our proposed solution differs from existing solutions by industry and academic communities. We demonstrates a functional AI model to triage by inferencing using a single x-ray image, while the AI model is trained using both X-ray and CT data. We report on how such a multi-modal training improves the solution compared to X-ray only training. The multi-modal solution increases the AUC (area under the receiver operating characteristic curve) from 0.89 to 0.93 for the classification between COVID-19 and non-COVID-19 cases. It also positively impacts the Dice coefficient (0.59 to 0.62) for segmenting the COVID-19 pathology.",
keywords = "Artificial intelligence, COVID-19, Multi-modal",
author = "Tao Tan and Bipul Das and Ravi Soni and Mate Fejes and Sohan Ranjan and Szabo, \{Daniel Attila\} and Vikram Melapudi and Shriram, \{K. S.\} and Utkarsh Agrawal and Laszlo Rusko and Zita Herczeg and Barbara Darazs and Pal Tegzes and Lehel Ferenczi and Rakesh Mullick and Gopal Avinash",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 ; Conference date: 27-09-2021 Through 01-10-2021",
year = "2021",
doi = "10.1007/978-3-030-87234-2\_31",
language = "English",
isbn = "9783030872335",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "325--334",
editor = "\{de Bruijne\}, Marleen and Cattin, \{Philippe C.\} and St{\'e}phane Cotin and Nicolas Padoy and Stefanie Speidel and Yefeng Zheng and Caroline Essert",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings",
address = "Germany",
}