TY  - JOUR
AU  - Wirkert, Sebastian
AU  - Kenngott, Hannes
AU  - Mayer, Benjamin
AU  - Mietkowski, Patrick
AU  - Wagner, Martin
AU  - Sauer, Peter
AU  - Clancy, Neil T
AU  - Elson, Daniel S
AU  - Maier-Hein, Lena
TI  - Robust near real-time estimation of physiological parameters from megapixel multispectral images with inverse Monte Carlo and random forest regression.
JO  - International journal of computer assisted radiology and surgery
VL  - 11
IS  - 6
SN  - 1861-6429
CY  - Berlin
PB  - Springer
M1  - DKFZ-2017-06024
SP  - 909 - 917
PY  - 2016
AB  - Multispectral imaging can provide reflectance measurements at multiple spectral bands for each image pixel. These measurements can be used for estimation of important physiological parameters, such as oxygenation, which can provide indicators for the success of surgical treatment or the presence of abnormal tissue. The goal of this work was to develop a method to estimate physiological parameters in an accurate and rapid manner suited for modern high-resolution laparoscopic images.While previous methods for oxygenation estimation are based on either simple linear methods or complex model-based approaches exclusively suited for off-line processing, we propose a new approach that combines the high accuracy of model-based approaches with the speed and robustness of modern machine learning methods. Our concept is based on training random forest regressors using reflectance spectra generated with Monte Carlo simulations.According to extensive in silico and in vivo experiments, the method features higher accuracy and robustness than state-of-the-art online methods and is orders of magnitude faster than other nonlinear regression based methods.Our current implementation allows for near real-time oxygenation estimation from megapixel multispectral images and is thus well suited for online tissue analysis.
KW  - Hemoglobins (NLM Chemicals)
KW  - Oxygen (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:27142459
C2  - pmc:PMC4893375
DO  - DOI:10.1007/s11548-016-1376-5
UR  - https://inrepo02.dkfz.de/record/130948
ER  -