[HTML][HTML] Surgical data science–from concepts toward clinical translation

L Maier-Hein, M Eisenmann, D Sarikaya, K März… - Medical image …, 2022 - Elsevier
Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Deep learning in medical hyperspectral images: A review

R Cui, H Yu, T Xu, X Xing, X Cao, K Yan, J Chen - Sensors, 2022 - mdpi.com
With the continuous progress of development, deep learning has made good progress in the
analysis and recognition of images, which has also triggered some researchers to explore …

[HTML][HTML] Robust deep learning-based semantic organ segmentation in hyperspectral images

S Seidlitz, J Sellner, J Odenthal, B Özdemir… - Medical Image …, 2022 - Elsevier
Semantic image segmentation is an important prerequisite for context-awareness and
autonomous robotics in surgery. The state of the art has focused on conventional RGB video …

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model

A Studier-Fischer, S Seidlitz, J Sellner, B Özdemir… - Scientific Reports, 2022 - nature.com
Visual discrimination of tissue during surgery can be challenging since different tissues
appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by …

Spectral imaging enables contrast agent–free real-time ischemia monitoring in laparoscopic surgery

L Ayala, TJ Adler, S Seidlitz, S Wirkert, C Engels… - Science …, 2023 - science.org
Laparoscopic surgery has evolved as a key technique for cancer diagnosis and therapy.
While characterization of the tissue perfusion is crucial in various procedures, such as partial …

Spectral organ fingerprints for intraoperative tissue classification with hyperspectral imaging

A Studier-Fischer, S Seidlitz, J Sellner, M Wiesenfarth… - bioRxiv, 2021 - biorxiv.org
Visual discrimination of tissue during surgery can be challenging since different tissues
appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by …

New spectral imaging biomarkers for sepsis and mortality in intensive care

S Seidlitz, K Hölzl, A von Garrel, J Sellner… - arXiv preprint arXiv …, 2024 - arxiv.org
With sepsis remaining a leading cause of mortality, early identification of septic patients and
those at high risk of death is a challenge of high socioeconomic importance. The driving …

[HTML][HTML] Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer

IC Wu, YC Chen, R Karmakar, A Mukundan, G Gabriel… - Biomedicines, 2024 - mdpi.com
Background/Objectives: Head and neck cancer (HNC), predominantly squamous cell
carcinoma (SCC), presents a significant global health burden. Conventional diagnostic …

Band selection for oxygenation estimation with multispectral/hyperspectral imaging

L Ayala, F Isensee, SJ Wirkert, AS Vemuri… - Biomedical Optics …, 2022 - opg.optica.org
Multispectral imaging provides valuable information on tissue composition such as
hemoglobin oxygen saturation. However, the real-time application of this technique in …

Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis

J Sellner, A Studier-Fischer, AB Qasim… - arXiv preprint arXiv …, 2024 - arxiv.org
Novel optical imaging techniques, such as hyperspectral imaging (HSI) combined with
machine learning-based (ML) analysis, have the potential to revolutionize clinical surgical …