Does Medical Imaging learn different Convolution Filters?
- Recent work has investigated the distributions of learned convolution filters through a large-scale study containing hundreds of heterogeneous image models. Surprisingly, on average, the distributions only show minor drifts in comparisons of various studied dimensions including the learned task, image domain, or dataset. However, among the studied image domains, medical imaging models appeared toRecent work has investigated the distributions of learned convolution filters through a large-scale study containing hundreds of heterogeneous image models. Surprisingly, on average, the distributions only show minor drifts in comparisons of various studied dimensions including the learned task, image domain, or dataset. However, among the studied image domains, medical imaging models appeared to show significant outliers through "spikey" distributions, and, therefore, learn clusters of highly specific filters different from other domains. Following this observation, we study the collected medical imaging models in more detail. We show that instead of fundamental differences, the outliers are due to specific processing in some architectures. Quite the contrary, for standardized architectures, we find that models trained on medical data do not significantly differ in their filter distributions from similar architectures trained on data from other domains. Our conclusions reinforce previous hypotheses stating that pre-training of imaging models can be done with any kind of diverse image data.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/6453 | Bibliografische Angaben |
Title (English): | Does Medical Imaging learn different Convolution Filters? |
Conference: | Medical Imaging meets NeurIPS Workshop : An official NeurIPS Workshop, 2 December 2022, New Orleans, Louisiana, United States of America |
Author: | Paul GavrikovStaff MemberORCiDGND, Janis KeuperStaff MemberORCiDGND |
Year of Publication: | 2022 |
First Page: | 1 |
Last Page: | 5 |
Parent Title (English): | Medical Imaging meets NeurIPS Workshop at NeurIPs 2022 |
DOI: | https://doi.org/10.48550/arXiv.2210.13799 |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
Forschung / IMLA - Institute for Machine Learning and Analytics | |
Institutes: | Bibliografie |
Tag: | Machine Learning | Formale Angaben |
Relevance: | Konferenzbeitrag: h5-Index < 30 |
Open Access: | Open Access |
Bronze | |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |
ArXiv Id: | http://arxiv.org/abs/2210.13799v1 |
ArXiv Id: | http://arxiv.org/abs/2210.13799 |