Search

Your search keyword '"Uckermann, Ortrud"' showing total 333 results
Start Over Author "Uckermann, Ortrud"
333 results on '"Uckermann, Ortrud"'

3. Learned end-to-end high-resolution lensless fiber imaging toward intraoperative real-time cancer diagnosis

Author

Wu, Jiachen, Wang, Tijue, Uckermann, Ortrud, Galli, Roberta, Schackert, Gabriele, Cao, Liangcai, Czarske, Jürgen, and Kuschmierz, Robert

Subjects
Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing, Physics - Optics
Abstract

Endomicroscopy is indispensable for minimally invasive diagnostics in clinical practice. For optical keyhole monitoring of surgical interventions, high-resolution fiber endoscopic imaging is considered to be very promising, especially in combination with label-free imaging techniques to realize in vivo diagnosis. However, the inherent honeycomb-artifacts of coherent fiber bundles (CFB) reduce the resolution and limit the clinical applications. We propose an end-to-end lensless fiber imaging scheme toward intraoperative real-time cancer diagnosis. The framework includes resolution enhancement and classification networks that use single-shot fiber bundle images to provide both high-resolution images and tumor diagnosis result. The well-trained resolution enhancement network not only recovers high-resolution features beyond the physical limitations of CFB, but also helps improving tumor recognition rate. Especially for glioblastoma, the resolution enhancement network helps increasing the classification accuracy from 90.8% to 95.6%. The novel technique can enable histological real-time imaging through lensless fiber endoscopy and is promising for rapid and minimal-invasive intraoperative diagnosis in clinics.

Published
2022

4. Coherent False Seizure Prediction in Epilepsy, Coincidence or Providence?

Author

Müller, Jens, Yang, Hongliu, Eberlein, Matthias, Leonhardt, Georg, Uckermann, Ortrud, Kuhlmann, Levin, and Tetzlaff, Ronald

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

Seizure forecasting using machine learning is possible, but the performance is far from ideal, as indicated by many false predictions and low specificity. Here, we examine false and missing alarms of two algorithms on long-term datasets to show that the limitations are less related to classifiers or features, but rather to intrinsic changes in the data. We evaluated two algorithms on three datasets by computing the correlation of false predictions and estimating the information transfer between both classification methods. For 9 out of 12 individuals both methods showed a performance better than chance. For all individuals we observed a positive correlation in predictions. For individuals with strong correlation in false predictions we were able to boost the performance of one method by excluding test samples based on the results of the second method. Substantially different algorithms exhibit a highly consistent performance and a strong coherency in false and missing alarms. Hence, changing the underlying hypothesis of a preictal state of fixed time length prior to each seizure to a proictal state is more helpful than further optimizing classifiers. The outcome is significant for the evaluation of seizure prediction algorithms on continuous data., Comment: 23 pages, 7 figures, accepted for publication in Clinical Neurophysiology

Published
2021

7. Prediction of WHO grade and methylation class of aggressive meningiomas: Extraction of diagnostic information from infrared spectroscopic data

Author

Galli, Roberta, primary, Lehner, Franz, additional, Richter, Sven, additional, Kirsche, Katrin, additional, Meinhardt, Matthias, additional, Juratli, Tareq A, additional, Temme, Achim, additional, Kirsch, Matthias, additional, Warta, Rolf, additional, Herold-Mende, Christel, additional, Ricklefs, Franz L, additional, Lamszus, Katrin, additional, Sievers, Philipp, additional, Sahm, Felix, additional, Eyüpoglu, Ilker Y, additional, and Uckermann, Ortrud, additional

Published
2024
Full Text
View/download PDF

9. Resolution-enhanced multi-core fiber imaging learned on a digital twin for cancer diagnosis.

Author

Tijue Wang, Dremel, Jakob, Richter, Sven, Polanski, Witold, Uckermann, Ortrud, Eyüpoglu, Ilker, Czarske, Jürgen W., and Kuschmierz, Robert

Subjects
DIGITAL twins, DEEP learning, IMAGE reconstruction, DIGITAL learning, SIGNAL-to-noise ratio
Abstract

Significance: Deep learning enables label-free all-optical biopsies and automated tissue classification. Endoscopic systems provide intraoperative diagnostics to deep tissue and speed up treatment without harmful tissue removal. However, conventional multi-core fiber (MCF) endoscopes suffer from low resolution and artifacts, which hinder tumor diagnostics. Aim: We introduce a method to enable unpixelated, high-resolution tumor imaging through a given MCF with a diameter of around 0.65 mm and arbitrary core arrangement and inhomogeneous transmissivity. Approach: Image reconstruction is based on deep learning and the digital twin concept of the single-reference-based simulation with inhomogeneous optical properties of MCF and transfer learning on a small experimental dataset of biological tissue. The reference provided physical information about the MCF during the training processes. Results: For the simulated data, hallucination caused by the MCF inhomogeneity was eliminated, and the averaged peak signal-to-noise ratio and structural similarity were increased from 11.2 dB and 0.20 to 23.4 dB and 0.74, respectively. By transfer learning, the metrics of independent test images experimentally acquired on glioblastoma tissue ex vivo can reach up to 31.6 dB and 0.97 with 14 fps computing speed. Conclusions: With the proposed approach, a single reference image was required in the pre-training stage and laborious acquisition of training data was bypassed. Validation on glioblastoma cryosections with transfer learning on only 50 image pairs showed the capability for high-resolution deep tissue retrieval and high clinical feasibility. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

14. Evaluation of machine learning methods for seizure prediction in epilepsy

Author

Eberlein Matthias, Müller Jens, Yang Hongliu, Walz Simon, Schreiber Janina, Tetzlaff Ronald, Creutz Susanne, Uckermann Ortrud, and Leonhardt Georg

Subjects
epilepsy, seizure forecasting, seizure prediction, machine learning, deep learning, Medicine
Abstract

Epilepsy affects about 50 million people worldwide of which one third is refractory to medication. An automated and reliable system that warns of impending seizures would greatly improve patient’s quality of life by overcoming the uncertainty and helplessness due to the unpredicted events. Here we present new seizure prediction results including a performance comparison of different methods. The analysis is based on a new set of intracranial EEG data that has been recorded in our working group during presurgical evaluation. We applied two different methods for seizure prediction and evaluated their performance pseudoprospectively. The comparison of this evaluation with common statistical evaluation reveals possible reasons for overly optimistic estimations of the performance of seizure forecasting systems.

Published
2019
Full Text
View/download PDF

23. A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition

Author

Steiner, Gerald, primary, Galli, Roberta, additional, Preusse, Grit, additional, Michen, Susanne, additional, Meinhardt, Matthias, additional, Temme, Achim, additional, Sobottka, Stephan B., additional, Juratli, Tareq A., additional, Koch, Edmund, additional, Schackert, Gabriele, additional, Kirsch, Matthias, additional, and Uckermann, Ortrud, additional

Published
2022
Full Text
View/download PDF

27. Combined Brillouin and Raman system for biomedical applications

Author

Rix Jan, Koch Edmund, Kirsch Matthias, Schackert Gabriele, Uckermann Ortrud, and Galli Roberta

Subjects
Physics, QC1-999
Abstract

A VIPA based Brillouin spectrometer consisting of commercially available components has been combined with a standard Raman spectrometer and a confocal microscope allowing simultaneous and co-localized measurements of biological samples and tissues.

Published
2020
Full Text
View/download PDF

32. Intraoperative in-situ Raman Spektroskopie zur Abgrenzung von Hirntumoren

Author

Richter, Sven, Ziegler, Jonathan, Juratli, Tareq, Sobottka, Stephan B., Galli, Roberta, Steiner, Gerald, Kirsch, Matthias, Schackert, Gabriele, and Uckermann, Ortrud

Subjects
ddc: 610, Medicine and health
Abstract

Objective: Maximal safe tumor resection (MTR) is one of the biggest challenges in Neurosurgery. Raman spectroscopy could be utilized to achieve MTR, since it is a label-free technique to acquire a biochemical fingerprint of tissue within seconds. However, clinical translation to intraoperative settings [for full text, please go to the a.m. URL]

Published
2022

33. Highly sensitive and quick in ovo sexing of domestic chicken eggs by two-wavelength fluorescence spectroscopy

Author

Preuße, Grit, Porstmann, Vincenz, Bartels, Thomas, Schnabel, Christian, Galli, Roberta, Koch, Edmund, Oelschlägel, Martin, Uckermann, Ortrud, Steiner, Gerald, Preuße, Grit, Porstmann, Vincenz, Bartels, Thomas, Schnabel, Christian, Galli, Roberta, Koch, Edmund, Oelschlägel, Martin, Uckermann, Ortrud, and Steiner, Gerald

Abstract

The in ovo sexing of chicken eggs is a current task and a prerequisite to overcome the mass killing of male day-old chicks from laying lines. Although various methods have been developed and tested in recent years, practicable methods for sex determination are still missing which can be applicated in poultry hatcheries before the chicken embryo is capable of nociception and pain sensation. Optical spectroscopic methods enable an early determination of the sex. In this study, a novel method based on two-wavelength in ovo fluorescence excitation is described. More than 1600 eggs were examined. In ovo fluorescence was sequentially excited at 532 nm and 785 nm. The fluorescence intensities of the spectral regions behave inversely with respect to sex. It is shown that the observed sex-related differences in the fluorescence intensities are based on the embryonic hemoglobin synthesis. The accuracy of sex determination is 96% for both sexes. The hatching rate is not reduced compared to an equivalent reference group.

Published
2022

34. A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition

Author

Steiner, Gerald, Galli, Roberta, Preusse, Grit, Michen, Susanne, Meinhardt, Matthias, Temme, Achim, Sobottka, Stephan B., Juratli, Tareq A., Koch, Edmund, Schackert, Gabriele, Kirsch, Matthias, Uckermann, Ortrud, Steiner, Gerald, Galli, Roberta, Preusse, Grit, Michen, Susanne, Meinhardt, Matthias, Temme, Achim, Sobottka, Stephan B., Juratli, Tareq A., Koch, Edmund, Schackert, Gabriele, Kirsch, Matthias, and Uckermann, Ortrud

Abstract

Purpose: Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition. Methods: Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors. Results The model correctly classified 82% (517/628) of specimens as “tumor” or “non-tumor”, respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified. Conclusion: The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.

Published
2022

41. Infrarotspektroskopie zur schnellen, operationsbegleitenden Analyse von nativen Hirntumorbiopsien - eine Studie mit 821 Patienten

Author

Uckermann, Ortrud, Galli, Roberta, Schackert, Gabriele, Steiner, Gerald, and Kirsch, Matthias

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Objective: Optical biopsies were suggested for intraoperative brain tumor delineation and diagnosis. Particularly, infrared spectroscopy was shown to identify primary and secondary brain tumors, and is well compatible with clinical routines, as it is fast, label-free and robust. However, studies have[for full text, please go to the a.m. URL], 72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie

Published
2021
Full Text
View/download PDF

47. Shotgun lipidomics-based characterization of the landscape of lipid metabolism in colorectal cancer

Author

Wang, Yuting, primary, Hinz, Sebastian, additional, Uckermann, Ortrud, additional, Hönscheid, Pia, additional, von Schönfels, Witigo, additional, Burmeister, Greta, additional, Hendricks, Alexander, additional, Ackerman, Jacobo Miranda, additional, Baretton, Gustavo B., additional, Hampe, Jochen, additional, Brosch, Mario, additional, Schafmayer, Clemens, additional, Shevchenko, Andrej, additional, and Zeissig, Sebastian, additional

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results