@inproceedings{WohlschlaegerLeiterDietlmeieretal.2023, author = {Wohlschl{\"a}ger, Maximilian and Leiter, Nina and Dietlmeier, Maximilian and L{\"o}der, Martin G.J. and Versen, Martin and Laforsch, Christian}, title = {Comparison of Two Classification Methods Trained with FD-FLIM Data to Identify and Distinguish Plastics from Environmental Materials}, series = {2023 International Joint Conference on Neural Networks (IJCNN)}, booktitle = {2023 International Joint Conference on Neural Networks (IJCNN)}, doi = {10.1109/IJCNN54540.2023.10191054}, pages = {1 -- 9}, year = {2023}, abstract = {Previous research on identifying plastic types and differentiating plastics from environmental material is promising by utilizing the specific fluorescence lifetime, but the evaluation still has to be automated. Therefore, an automated Gaussian analysis is developed for evaluating frequency-domain fluorescence lifetime images of plastics and environmental materials. Furthermore, we applied a "Multilayer Perceptron" and "Random Forest Classifier" to the data resulting from the Gaussian analysis of the frequency domain fluorescence lifetime imaging microscopy data. The classification results show high F1-scores, whereby the best "Multilayer Perceptron" and "Random Forest Classifier" achieved an F1-score of 90\%. Thus, identifying and differentiating plastics and environmental materials is possible by applying a "Multilayer Perceptron" or "Random Forest Classifier" to the Gaussian-analyzed imaged fluorescence lifetime data.}, language = {en} } @inproceedings{LeiterDietlmeierWohlschlaegeretal.2023, author = {Leiter, Nina and Dietlmeier, Maximilian and Wohlschl{\"a}ger, Maximilian and L{\"o}der, Martin G.J. and Versen, Martin and Laforsch, Christian}, title = {Development of a Neural Network for Automatic Classification of Post-Consumer Wood Using Rapid-FLIM}, series = {2023 IEEE Sensors Applications Symposium (SAS)}, booktitle = {2023 IEEE Sensors Applications Symposium (SAS)}, doi = {10.1109/SAS58821.2023.10254174}, pages = {1 -- 6}, year = {2023}, abstract = {The economic use of wood is a growing sector, not only because of the significant advantage of wood to retain CO 2 . It is crucial to increase the material recycling of wood in several lifecycles, but currently, there is no reliable post-consumer wood sorting technique in line. This research measures 365 post-consumer wood samples of classes A1-4 four times with the frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) subset method rapid fluorescence lifetime imaging microscopy (Rapid-FLIM). The data is analyzed on their statistical features. Four neural networks based on Multilayer perceptron are then trained and tested with twelve statistical features extracted from the Rapid-FLIM images. The best model for this application contains the optimizer RMSprop, the activation function SELU and the loss function binary crossentropy. The best model of this structure could achieve a false positive ratio of 4.79 \% over the ten folds.}, language = {en} } @inproceedings{LeiterWohlschlaegerDietlmeieretal.2023, author = {Leiter, Nina and Wohlschl{\"a}ger, Maximilian and Dietlmeier, Maximilian and Versen, Martin and L{\"o}der, Martin and Laforsch, Christian}, title = {Comparative Analysis of Fluorescence Properties of Post-Consumer Wood Using FD-FLIM}, series = {2023 IEEE Sensors Applications Symposium (SAS)}, booktitle = {2023 IEEE Sensors Applications Symposium (SAS)}, doi = {10.1109/SAS58821.2023.10254052}, pages = {1 -- 6}, year = {2023}, abstract = {The FD-FLIM technique has a high potential for automated post-consumer wood sorting. A problem of analysing post-consumer wood fluorescence properties is the uncertainty of the post-consumer wood category as the origin of the samples are unknown. In this study, the fluorescence properties of actual post-consumer wood is compared with prepared wood samples. The post-consumer wood samples display slightly different fluorescence intensities and lifetimes due to environmental influences and a higher sample diversity. For improved training of evaluation algorithms for post-consumer wood sorting, the prepared sample set should be extended or the post-consumer wood should be additionally analysed in the laboratory.}, language = {en} } @inproceedings{WohlschlaegerVersenLaforsch2022, author = {Wohlschl{\"a}ger, Maximilian and Versen, Martin and Laforsch, Christian}, title = {Investigation of the Impact of CaCO3 Concentrations on the Fluorescence Lifetime of Polypropylene}, series = {2022 Conference on Lasers and Electro-Optics (CLEO)}, booktitle = {2022 Conference on Lasers and Electro-Optics (CLEO)}, pages = {1 -- 2}, year = {2022}, abstract = {The impact of fillers on the fluorescence lifetime of polymers is still unknown. Investigating polypropylene containing different CaCO 3 concentrations using FD-FLIM show an exponential increase in fluorescence lifetime proportional to the CaCO 3 density in polypropylene.}, language = {en} } @inproceedings{LeiterWohlschlaegerVersen2022, author = {Leiter, Nina and Wohlschl{\"a}ger, Maximilian and Versen, Martin}, title = {Frequency-domain fluorescence lifetime imaging as method to analyze wood structures}, series = {Conference on Lasers and Electro-Optics}, booktitle = {Conference on Lasers and Electro-Optics}, organization = {Technical Digest Series (Optica Publishing Group, 2022)}, doi = {10.1364/CLEO_AT.2022.JW3A.19}, pages = {JW3A.19}, year = {2022}, abstract = {The analysis of wood structures using FD-FLIM seems promising for the identification of wood at 488 nm, as lignin has a high impact on the fluorescence lifetime.}, language = {en} } @inproceedings{WohlschlaegerVersenLaforsch2022, author = {Wohlschl{\"a}ger, Maximilian and Versen, Martin and Laforsch, Christian}, title = {Investigation of the Impact of CaCO3 Concentrations on the Fluorescence Lifetime of Polypropylene}, series = {Conference on Lasers and Electro-Optics}, booktitle = {Conference on Lasers and Electro-Optics}, organization = {Technical Digest Series (Optica Publishing Group, 2022)}, doi = {10.1364/CLEO_AT.2022.AM2M.2}, pages = {AM2M.2}, year = {2022}, abstract = {The impact of fillers on the fluorescence lifetime of polymers is still unknown. Investigating polypropylene containing different CaCO3 concentrations using FD-FLIM show an exponential increase in fluorescence lifetime proportional to the CaCO3 density in polypropylene.}, language = {en} } @inproceedings{WohlschlaegerKhanLeiteretal.2023, author = {Wohlschl{\"a}ger, Maximilian and Khan, Yamna and Leiter, Nina and Versen, Martin and L{\"o}der, Martin and Laforsch, Christian}, title = {Combining BLOB-Detection and MLP to Detect and Identify Plastics in an Environmental Matrix}, series = {2023 IEEE Sensors Applications Symposium (SAS)}, booktitle = {2023 IEEE Sensors Applications Symposium (SAS)}, doi = {10.1109/SAS58821.2023.10254171}, pages = {1 -- 5}, year = {2023}, abstract = {Environmental pollution by plastics is an increasing problem. However, state-of-the-art methods have significant disadvantages in detecting and identifying plastics directly in an environmental matrix. In this study, we propose a blob detection algorithm in combination with a neural network for fast and automated identification of plastics and non-plastics in a single fluorescence lifetime image. Therefore an artificial environmental matrix is prepared that contains soil, grass, spruce and HDPE (high density polyethylene) particles. Several FD-FLIM (frequency domain fluorescence lifetime imaging microscopy) images are taken, and the detection algorithm and the neural network are applied. We successfully demonstrated the suitability of the thresholding algorithm and the binary classification of the HDPE particles directly in the environmental matrix.}, language = {en} } @article{VersenWohlschlaegerLanghalsetal.2024, author = {Versen, Martin and Wohlschl{\"a}ger, Maximilian and Langhals, Heinz and Laforsch, Christian}, title = {The detection of organic polymers as contaminants in foodstuffs by means of the fluorescence decay of their auto fluorescence}, series = {Food and Humanity}, volume = {3}, journal = {Food and Humanity}, doi = {10.1016/j.foohum.2024.100363}, year = {2024}, abstract = {Products such as food can become contaminated during their manufacture or afterwards. Depending on the type of substance causing the contamination, these contaminants can be harmful to health and difficult to detect by visible inspection. The suitability of fluorescence decay and FD-FLIM for the detection of plastics contamination in foodstuffs is demonstrated. Therefore, a procedure for the detection of contaminating organic polymers (plastics) in processed meat such as salami by means of the fluorescence decay time of auto fluorescence is described. The auto fluorescence of processed meat was found to decay according to first order with a typical time constant of about 2 ns, whereas the time constant of significant polymers for the processing of meat is generally appreciably higher (2.5 ns - 5.5 ns depending on the polymer). As a consequence, contaminating organic polymers can not only be globally detected by means of the fluorescence decay but also localised in two-dimensional imaging. The present study reports a high potential of FD-FLIM for rapidly identifying and differentiating different plastics on and in different foodstuffs. The method allows an improved quality control of foodstuffs.}, language = {en} }