Explainable AI with Domain Adapted FastCAM for Endoscopy Images
- Enormous potential of artificial intelligence (AI) exists in numerous products and services, especially in healthcare and medical technology. Explainability is a central prerequisite for certification procedures around the world and the fulfilment of transparency obligations. Explainability tools increase the comprehensibility of object recognition in images using Convolutional Neural Networks, but lack precision. This paper adapts FastCAM for the domain of detection of medical instruments in endoscopy images. The results show that the Domain Adapted (DA)-FastCAM provides better results for the focus of the model than standard FastCAM weights.
| Author: | Jan StodtORCiDGND, Christoph ReichORCiDGND, Nathan Clarke |
|---|---|
| DOI: | https://doi.org/10.1007/978-3-031-08757-8_6 |
| ISBN: | 978-3-031-08757-8 |
| Parent Title (English): | Computational Science – ICCS 2022 : 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part III |
| Publisher: | Springer |
| Place of publication: | Cham |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Completion: | 2022 |
| Release Date: | 2022/08/29 |
| Tag: | CNN; Endoscopy; FastCAM; Healthcare; XAI |
| First Page: | 57 |
| Last Page: | 64 |
| Licence (German): |  Urheberrechtlich geschützt |