Feasibility of Dose Reduction in the Context of Preoperative Diagnostics in Cochlear Implant Surgery With a Photon-Counting Detector CT and Deep Learning-Supported Denoising
PCD-CT enables significant dose reduction for CI planning, with reliable CDL accuracy down to 50%. Deep learning denoising enhances image quality but is less effective below 50%, necessitating manual segmentation. These findings align with ALARA principles and suggest further refinement of AI algorithms for lower-dose applicability in CI diagnostics.
Authors
- Thore Schade‐Mann (ORCID: https://orcid.org/0000-0002-4724-2440)
- Bernhard Hirt (ORCID: https://orcid.org/0000-0002-6018-7191)
- Andreas Brendlin (ORCID: https://orcid.org/0000-0002-5961-9727)
- Anke Tropitzsch
- Sven Becker (ORCID: https://orcid.org/0000-0003-1972-3797)
- Judith Herrmann (ORCID: https://orcid.org/0000-0003-1535-8980)
- Peter Martus (ORCID: https://orcid.org/0000-0002-5386-5732)
- Friederike Bärhold (ORCID: https://orcid.org/0009-0009-8812-916X)
- Tobias Albrecht (ORCID: https://orcid.org/0000-0001-5564-5621)
- Hubert Löwenheim (ORCID: https://orcid.org/0000-0001-8200-8804)
- Agnes Mühle
- Saif Afat
Institutions
- Boston Children's Hospital (US)
- Harvard University (US)
- Zimmer Biomet (Netherlands) (NL)
- University of Tübingen (DE)
Publication Details
- Journal
- Otology & Neurotology
- Published
- 2025-10-24
- DOI
- https://doi.org/10.1097/mao.0000000000004647
- Primary Topic
- Radiation Dose and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00