Influence of preprocessing of stimulated Raman scattering images on the performance of deep neural networks for detecting cancer tissue
This study shows that preprocessing of pixel values of stimulated Raman scattering images can have a great impact on the performance and the stability of deep learning algorithms when applied for classification of cancer tissue.
Authors
- Bernward Passlick (ORCID: https://orcid.org/0000-0002-4684-0625)
- Kathrin Enderle-Ammour
- Andreas Weber⋆ (ORCID: https://orcid.org/0000-0001-5624-3368)
- Marc Christian Metzger (ORCID: https://orcid.org/0000-0002-4893-7594)
- Rainer Schmelzeisen (ORCID: https://orcid.org/0000-0002-9686-6989)
- Uyen‐Thao Le (ORCID: https://orcid.org/0000-0002-5671-3048)
- Birte Ohm (ORCID: https://orcid.org/0000-0001-8591-0473)
- Martin Werner (ORCID: https://orcid.org/0000-0003-4638-1251)
- Leonard Simon Brandenburg (ORCID: https://orcid.org/0000-0003-4697-5287)
- Jakob Straehle (ORCID: https://orcid.org/0000-0003-3063-8972)
- Mohamed Khalafalla Hassan (ORCID: https://orcid.org/0000-0002-6238-8915)
- David Steybe (ORCID: https://orcid.org/0000-0003-3885-6659)
- Peter Bronsert (ORCID: https://orcid.org/0000-0001-8558-0347)
- Jürgen Beck (ORCID: https://orcid.org/0000-0001-8794-9320)
- Severin Schmid (ORCID: https://orcid.org/0000-0001-8077-082X)
- K. Schröder
Institutions
- University of Freiburg (DE)
- University Medical Center Freiburg (DE)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-08-21
- DOI
- https://doi.org/10.21037/qims-2024-2608
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00