Auswahl der wissenschaftlichen Literatur zum Thema „Synergistic reconstruction“

Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist–Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial–temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

This special issue is the second part of a themed issue that focuses on synergistic tomographic image reconstruction and includes a range of contributions in multiple disciplines and application areas. The primary subject of study lies within inverse problems which are tackled with various methods including statistical and computational approaches. This volume covers algorithms and methods for a wide range of imaging techniques such as spectral X-ray computed tomography (CT), positron emission tomography combined with CT or magnetic resonance imaging, bioluminescence imaging and fluorescence-mediated imaging as well as diffuse optical tomography combined with ultrasound. Some of the articles demonstrate their utility on real-world challenges, either medical applications (e.g. motion compensation for imaging patients) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issues is to bring together different scientific communities which do not usually interact as they do not share the same platforms such as journals and conferences. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

Conventional magnetic resonance imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction—addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report on our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

This work considers synergistic multi-spectral CT reconstruction where information from all available energy channels is combined to improve the reconstruction of each individual channel. We propose to fuse these available data (represented by a single sinogram) to obtain a polyenergetic image which keeps structural information shared by the energy channels with increased signal-to-noise ratio. This new image is used as prior information during a channel-by-channel minimization process through the directional total variation. We analyse the use of directional total variation within variational regularization and iterative regularization. Our numerical results on simulated and experimental data show improvements in terms of image quality and in computational speed. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF’s recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF’s integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

The aroma of an instant white tea (IWT) was extracted through simultaneous distillation–extraction (SDE) and analyzed by sensory evaluation, gas chromatography-mass spectrometry-olfactometry (GC-MS-O), aroma reconstruction, omission test and synergistic interaction analysis. Sensory evaluation showed the IWT was dominated with floral and sweet notes. The SDE extract had the aroma similar to the IWT. The main volatile components in the SDE extract were benzyl alcohol, linalool, hotrienol, geraniol, α-terpineol, coumarin, camphene, benzeneacetaldehyde, 2-hexanone, cis-jasmin lactone and phenylethyl alcohol. GC-MS-O and aroma reconstruction experiments showed 16 aroma-active compounds. Linalool, trans-β-damascenone and camphene were the major contributors to floral, sweet and green notes based on flavor dilution analysis and omission test. Linalool and trans-β-damascenone had synergistic effect to promote floral and sweet notes. Camphene and trans-β-damascenone had synergistic effect to reduce green and sweet notes. The study helps to understand the aroma of IWT and antagonism interactions among aroma-active volatiles.

Imaging is omnipresent in modern society with imaging devices based on a zoo of physical principles, probing a specimen across different wavelengths, energies and time. Recent years have seen a change in the imaging landscape with more and more imaging devices combining that which previously was used separately. Motivated by these hardware developments, an ever increasing set of mathematical ideas is appearing regarding how data from different imaging modalities or channels can be synergistically combined in the image reconstruction process, exploiting structural and/or functional correlations between the multiple images. Here we review these developments, give pointers to important challenges and provide an outlook as to how the field may develop in the forthcoming years. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 1’.

The objective of this study was to assess if new cloud datasets, namely horizontal fields of integrated cloud parameters and transects of cloud profiles becoming available from current and future satellites like MODIS and CloudSAT as well as EarthCARE will allow for the reconstruction of three-dimensional cloud fields. Because three-dimensional measured cloud fields do not exist, surrogate cloud fields were used to develop and test reconstruction techniques. In order to answer the question if surrogate cloud fields may represent real cloud fields and to evaluate potential constraints for cloud field reconstruction, statistics of surrogate cloud fields have been compared to statistics of various remote sensing retrievals. It has turned out that except for cloud droplet effective radius, which is too low, other cloud parameters are in line with parameters derived from measurements. The reconstruction approach is divided into two parts. The first one deals with the reconstruction of the cloud fields. Three techniques with varying complexity are presented constraining the reconstruction by measurements to various degrees. Whereas the first one applies only information of a satellite radiometer, the other two constrain the retrieval also by profile information measured within the domain. Comparing the reconstruction quality of the approaches, there is no superior algorithm performing better for all cloud fields. This might be ascribed to liquid water content profiles of the surrogate cloud fields close to their adiabatic reference. Consequently, the assumption of adiabatic liquid water content profiles of the first scheme yields adequate estimates and additional information from profiles does not improve the reconstruction. The second part of the reconstruction approach addresses the reconstruction quality by comparing parameters of radiative transfer describing photon path statistics as well as reflectances. Therefore three-dimensional radiative transfer simulations with a Monte Carlo code were carried out for the surrogate cloud fields as well as for the reconstructed cloud fields. It was assumed that deviations of the parameter simulated for the reconstructed cloud and the surrogate cloud field are smaller when reconstruction is more accurate. For parameter describing photon pathes it has been found that only deviations of geometrical pathlength statistics reflect the reconstruction quality to a certain degree. Deviations of other parameters like photon penetration depth do not allow for either assessing local differences in reconstruction quality by an individual reconstruction scheme or to infer the most appropriate reconstruction scheme. The differences in reflectances do also not enable to evaluate reconstruction quality. They prevent from gaining insight in local accuracy of reconstruction due to effects like horizontal photon transport weakening the relations between microphysical as well as optical properties and reflectances of the column. In order to address these effects, grids of various complexity, derived by applying photon path properties, were used to weight deviations of cloud properties when analyzing the relationships. Unfortunately, there is no increase of explained variance due to the application of the weighting grids. Additionally, the sensitivity of the results to the model set-up, namely the spatial resolution of the cloud fields as well as the simplification and neglection of ancillary parameters, were analyzed. Though one would assume a strengthening of relationships between deviations of cloud parameters and deviations of reflectances due to more reliable sampling and reduced inter-column transport of photons when column size increases, there is no indication for resolutions where an assessment of the reconstruction quality by means of reflectance deviations becomes feasible. It also has been shown that inappropriate treatment of aerosols in the radiative transfer simulation impose an error comparable in magnitude to differences in reflectances due to inaccurate cloud field reconstruction. This is especially the case when clouds are located in the boundary layer of the aerosol model. Consequently, appropriate aerosol models should be applied in the analysis. May be due to the low surface reflection and the high cloud optical depths, the representation of the surface reflection function seems to be of minor importance. Summarizing the results, differences in radiative transfer do not allow for the assessment of cloud field reconstruction quality. In order to accomplish the task of cloud field reconstruction, the reconstruction part could be constrained employing information from additional measurements. Observational geometries enabling to use tomographic methods and the application of additional wavelengths for validation might help, too
Ziel der Arbeit war die Evaluierung inwieweit Datensätze von Wolkenparametern, horizontale Felder integraler Wolkenparameter und Schnitte vertikal aufgelöster Parameter, zur Rekonstruktion dreidimensionaler Wolkenfelder genutzt werden können. Entsprechende Datensätze sind durch MODIS und CloudSAT erstmals vorhanden und werden zusätzlich mit dem Start von EarthCARE zur Verfügung stehen. Da dreidimensionale Wolkenfelder aus Messungen nicht existieren, wurden zur Entwicklung der Rekonstruktionsmethoden surrogate Wolkenfelder genutzt. Um die Qualität der surrogaten Wolkenfelder abzuschätzen und um mögliche Randbedingungen zur Rekonstruktion aufzuzeigen, wurden Statistiken der surrogaten Wolkenfelder mit denen unterschiedlicher Fernerkundungsprodukte verglichen. Dabei zeigte sich, dass, abgesehen von den gegenüber Messungen zu geringen Effektivradien der Wolkentropfen in den surrogaten Wolkenfeldern, die übrigen Wolkenparameter gut übereinstimmen. Der Rekonstruktionsansatz gliedert sich in zwei Teile. Der erste Teil beinhaltet die Rekonstruktion der Wolkenfelder. Dazu werden drei Techniken unterschiedlicher Komplexität genutzt, wobei die Komplexität durch den Grad der eingebundenen Messungen bestimmt wird. Während die einfachste Technik lediglich Informationen, wie sie aus Messungen mit einem Satellitenradiometer gewonnen werden können, nutzt, binden die anderen Techniken zusätzlich Profilinformationen aus dem beobachteten Gebiet ein. Analysen zeigten, dass keine der Methoden für alle untersuchten Wolkenfelder den anderen Methoden überlegen ist. Dies mag daran liegen, dass die Flüssigwasserprofile der surrogaten Wolkenfelder nur geringfügig von den in der ersten Rekonstruktionsmethode angenommenen adiabatischen Flüssigwasserprofilen abweichen, so dass die Nutzung der Profile kaum zusätzliche Information für die Rekonstruktion liefert. Im zweiten Teil des Rekonstruktionsansatzes wird die Qualität der rekonstruierten Wolkenfelder durch den Vergleich von Parametern des Strahlungstransfers, wie Photonenpfad-Statistiken und Strahlungsgrößen, evaluiert. Dazu wurden sowohl für die surrogaten Wolkenfelder als auch für die rekonstruierten Wolkenfelder dreidimensionale Strahlungstransfersimulationen mit einem Monte-Carlo-Modell durchgeführt. Angenommen wurde hierbei, dass eine bessere Rekonstruktionsqualität durch geringere Abweichungen der betrachteten Strahlungsparameter aus Simulationen mit rekonstruierten und surrogaten Wolkenfeldern gekennzeichnet ist. Bei den Parametern, die die Photonenwege beschreiben, unterstützen lediglich die Abweichungen der geometrischen Photonenweglängen diese These. Weder erlauben die Abweichungen der übrigen Parameter, zum Beispiel der Eindringtiefen, Rückschlüsse auf die lokale Rekonstruktionsqualität der einzelnen Methoden zu ziehen, noch ermöglichen sie die beste Rekonstruktionsmethode zu identifizieren. Auch die Unterschiede der simulierten Reflektanzen können nicht zur Bestimmung der Rekonstruktionsqualität herangezogen werden. Durch Effekte wie horizontale Photonentransporte werden die Zusammenhänge zwischen mikrophysikalischen und optischen Eigenschaften und Reflektanzen der jeweiligen Gittersäule aufgeweicht, und folglich sind keine Rückschlüsse auf die lokale Rekonstruktionsqualität möglich. Um auf entsprechende Effekte einzugehen, wurden für die Analyse Wichtungsfelder unterschiedlicher Komplexität aus Photonenwegeigenschaften generiert, um diese zur Wichtung der Abweichungen der Wolkeneigenschaften zu nutzen. Der Anteil der erklärten Varianz konnte jedoch durch die Nutzung der entsprechenden Wichtungsfelder nicht erhöht werden. Zusätzlich wurden Sensitivitätsstudien hinsichtlich einzelner Vorgaben der Untersuchung durchgeführt. Dazu wurden sowohl der Einfluss der räumlichen Auflösung der Wolkenfelder als auch die Vereinfachung oder Nichtbetrachtung einzelner Modellparameter analysiert. Eine Reduzierung der Auflösung einhergehend mit einem zuverlässigeren Sampling und reduzierten Photonentransport zwischen den Gittersäulen führte zu keinem direkteren Zusammenhang zwischen den Abweichungen der Reflektanzen und den Abweichungen der mikrophysikalischen Eigenschaften. Folglich existiert keine Auflösung, die die Anwendung des Verfahrens ermöglichen würde. Ebenso wurde gezeigt, dass die unzureichende Einbeziehung von Aerosolen bei den Strahlungstransfersimulationen einen Fehler verursachen kann, der in der Größe dem Unterschied der Reflektanzen unzureichender Wolkenfeldrekonstruktionen gleichkommt. Dies ist insbesondere der Fall, wenn die Wolken sich innerhalb der Grenzschicht des Aerosolmodells befinden. Entspechend sollte in solchen Situationen dem verwendeten Aerosolmodell besondere Beachtung geschenkt werden. Hingegen ist der Einfluss des Ansatzes, wie die Bodenreflektion beschrieben wird, eher gering. Dies mag an dem verwendeten Modell mit einer geringen Albedo in Kombination mit optisch dicken Wolken liegen. Zusammenfassend kann festgestellt werden, dass die Unterschiede im Strahlungstransfer nicht zur Abschätzung der Rekonstruktionsqualität der Wolkenfelder herangezogen werden können. Um dem Ziel einer dreidimensionalen Wolkenfeldrekonstruktion näher zu kommen, könnten beim Rekonstruktionsteil Informationen aus zusätzlichen Messungen als Vorgaben genutzt werden. Ebenso könnten Beobachtungsgeometrien, welche die Anwendung tomographischer Methoden erlauben, sowie zusätzliche Wellenlängen zur Validierung der Rekonstruktionsergebnisse verwendet werden

La tomodensitométrie se concentre sur deux sujets clés : la réduction de la dose de radiation et l’imagerie multi-énergétique, qui sont interconnectés. La tomodensitométrie spectrale, une avancée émergente, capture des données sur plusieurs énergies de rayons X pour mieux distinguer les matériaux, minimisant le besoin de scans répétés et ainsi réduisant l’exposition globale aux radiations.Cependant, la réduction du nombre de photons dans chaque bin d’énergie rend les méthodes de reconstruction traditionnelles sensibles au bruit. Ainsi, l’apprentissage profond, qui a montré un potentiel considérable dans l’imagerie médicale, est envisagé.Cette thèse introduit un nouveau terme de régularisation intégrant des réseaux de neurones convolutifs pour relier les bins d’énergie à une variable latente, exploitant l’ensemble des données des bins pour une reconstruction synergique. À titre de preuve de concept, nous proposons Uconnect et sa variante MHUconnect, utilisant respectivement U-Nets et un UNet à multi-têtes en tant que réseaux de neurones convolutifs, où l’image d’un bin d’énergie spécifique sert de variable latente pour l’apprentissage supervisé. Ces méthodes ont été validées comme étant plus performantes que plusieurs méthodes existantes dans les tâches de reconstruction et de débruitage
Computed tomography (CT), a cornerstone of diagnostic imaging, focuses on two contemporary topics: radiation dose reduction and multi-energy imaging, which are inherently interconnected. As an emerging advancement, spectral CT can capture data across a range of X-ray energies for bettermaterial differentiation, reducing the need for repeat scans and thereby lowering overall radiationexposure. However, the reduced photon count in each energy bin makes traditional reconstruction methods susceptible to noise. Therefore, deep learning (DL) techniques, which have shown great promise in medical imaging, are being considered. This thesis introduces a novel regularizationterm that incorporates convolutional neural networks (CNNs) to connect energy bins to a latent variable, leveraging all binned data for synergistic reconstruction. As a proof-of concept, we propose Uconnect and its variant MHUconnect, employing U-Nets and the multi-head U-Net, respectively, as the CNNs, with images at a specific energy bin serving as the latent variable for supervised learning.The two methods are validated to outperform several existing approaches in reconstruction and denoising tasks

L’adoption généralisée des scanners hybrides Tomographie à émission de positons (TEP)/Tomodensitométrie (TDM) a conduit à une augmentation significative de la disponibilité des données d’imagerie combinées TEP/TDM. Cependant, les méthodologies actuelles traitent souvent chaque modalité de manière indépendante, négligeant ainsi le potentiel d’amélioration de la qualité des images grâce à l’exploitation des informations anatomiques et fonctionnelles complémentaires propres à chaque modalité. Exploiter ces informations intermodales pourrait améliorer les reconstructions TEP et TDM en fournissant une vision synergique des détails anatomiques et fonctionnels. Cette thèse propose une méthode innovante de reconstruction synergique d’images médicales via des modèles génératifs multibranches. En exploitant des autoencodeurs variationnels (VAE) multi-branches, notre approche apprend conjointement des images TEP et TDM, assurant un débruitage efficace et une reconstruction haute-fidélité. Ce cadre améliore la qualité des images et ouvre de nouvelles perspectives pour l’imagerie médicale multimodale en contexte clinique et de recherche
The widespread adoption of hybrid Positron emission tomography (PET)/Computed tomography (CT) scanners has led to a significant increase in the availability of combined PET/CT imaging data. However, current methodologies often process each modality independently, overlooking the potential to enhance image quality by leveraging the complementary anatomical and functional information intrinsic to each modality. Exploiting intermodal information has the potential to improve both PET and CT reconstructions by providing a synergistic view of anatomical and functional details. This thesis introduces a novel approach for synergistic reconstruction of medical images using multi-branch generative models. By employing variational autoencoders (VAEs) with a multi-branch architecture, our model simultaneously learns from paired PET and CT images,allowing for effective joint denoising and highfidelity reconstruction of both modalities. Beyond improving image quality, this framework also paves the way for future advancements in multi-modal medical imaging, highlighting the transformative potential of integrated approaches for hybrid imaging modalities in clinical and research settings

The objective of this study was to assess if new cloud datasets, namely horizontal fields of integrated cloud parameters and transects of cloud profiles becoming available from current and future satellites like MODIS and CloudSAT as well as EarthCARE will allow for the reconstruction of three-dimensional cloud fields. Because three-dimensional measured cloud fields do not exist, surrogate cloud fields were used to develop and test reconstruction techniques. In order to answer the question if surrogate cloud fields may represent real cloud fields and to evaluate potential constraints for cloud field reconstruction, statistics of surrogate cloud fields have been compared to statistics of various remote sensing retrievals. It has turned out that except for cloud droplet effective radius, which is too low, other cloud parameters are in line with parameters derived from measurements. The reconstruction approach is divided into two parts. The first one deals with the reconstruction of the cloud fields. Three techniques with varying complexity are presented constraining the reconstruction by measurements to various degrees. Whereas the first one applies only information of a satellite radiometer, the other two constrain the retrieval also by profile information measured within the domain. Comparing the reconstruction quality of the approaches, there is no superior algorithm performing better for all cloud fields. This might be ascribed to liquid water content profiles of the surrogate cloud fields close to their adiabatic reference. Consequently, the assumption of adiabatic liquid water content profiles of the first scheme yields adequate estimates and additional information from profiles does not improve the reconstruction. The second part of the reconstruction approach addresses the reconstruction quality by comparing parameters of radiative transfer describing photon path statistics as well as reflectances. Therefore three-dimensional radiative transfer simulations with a Monte Carlo code were carried out for the surrogate cloud fields as well as for the reconstructed cloud fields. It was assumed that deviations of the parameter simulated for the reconstructed cloud and the surrogate cloud field are smaller when reconstruction is more accurate. For parameter describing photon pathes it has been found that only deviations of geometrical pathlength statistics reflect the reconstruction quality to a certain degree. Deviations of other parameters like photon penetration depth do not allow for either assessing local differences in reconstruction quality by an individual reconstruction scheme or to infer the most appropriate reconstruction scheme. The differences in reflectances do also not enable to evaluate reconstruction quality. They prevent from gaining insight in local accuracy of reconstruction due to effects like horizontal photon transport weakening the relations between microphysical as well as optical properties and reflectances of the column. In order to address these effects, grids of various complexity, derived by applying photon path properties, were used to weight deviations of cloud properties when analyzing the relationships. Unfortunately, there is no increase of explained variance due to the application of the weighting grids. Additionally, the sensitivity of the results to the model set-up, namely the spatial resolution of the cloud fields as well as the simplification and neglection of ancillary parameters, were analyzed. Though one would assume a strengthening of relationships between deviations of cloud parameters and deviations of reflectances due to more reliable sampling and reduced inter-column transport of photons when column size increases, there is no indication for resolutions where an assessment of the reconstruction quality by means of reflectance deviations becomes feasible. It also has been shown that inappropriate treatment of aerosols in the radiative transfer simulation impose an error comparable in magnitude to differences in reflectances due to inaccurate cloud field reconstruction. This is especially the case when clouds are located in the boundary layer of the aerosol model. Consequently, appropriate aerosol models should be applied in the analysis. May be due to the low surface reflection and the high cloud optical depths, the representation of the surface reflection function seems to be of minor importance. Summarizing the results, differences in radiative transfer do not allow for the assessment of cloud field reconstruction quality. In order to accomplish the task of cloud field reconstruction, the reconstruction part could be constrained employing information from additional measurements. Observational geometries enabling to use tomographic methods and the application of additional wavelengths for validation might help, too.
Ziel der Arbeit war die Evaluierung inwieweit Datensätze von Wolkenparametern, horizontale Felder integraler Wolkenparameter und Schnitte vertikal aufgelöster Parameter, zur Rekonstruktion dreidimensionaler Wolkenfelder genutzt werden können. Entsprechende Datensätze sind durch MODIS und CloudSAT erstmals vorhanden und werden zusätzlich mit dem Start von EarthCARE zur Verfügung stehen. Da dreidimensionale Wolkenfelder aus Messungen nicht existieren, wurden zur Entwicklung der Rekonstruktionsmethoden surrogate Wolkenfelder genutzt. Um die Qualität der surrogaten Wolkenfelder abzuschätzen und um mögliche Randbedingungen zur Rekonstruktion aufzuzeigen, wurden Statistiken der surrogaten Wolkenfelder mit denen unterschiedlicher Fernerkundungsprodukte verglichen. Dabei zeigte sich, dass, abgesehen von den gegenüber Messungen zu geringen Effektivradien der Wolkentropfen in den surrogaten Wolkenfeldern, die übrigen Wolkenparameter gut übereinstimmen. Der Rekonstruktionsansatz gliedert sich in zwei Teile. Der erste Teil beinhaltet die Rekonstruktion der Wolkenfelder. Dazu werden drei Techniken unterschiedlicher Komplexität genutzt, wobei die Komplexität durch den Grad der eingebundenen Messungen bestimmt wird. Während die einfachste Technik lediglich Informationen, wie sie aus Messungen mit einem Satellitenradiometer gewonnen werden können, nutzt, binden die anderen Techniken zusätzlich Profilinformationen aus dem beobachteten Gebiet ein. Analysen zeigten, dass keine der Methoden für alle untersuchten Wolkenfelder den anderen Methoden überlegen ist. Dies mag daran liegen, dass die Flüssigwasserprofile der surrogaten Wolkenfelder nur geringfügig von den in der ersten Rekonstruktionsmethode angenommenen adiabatischen Flüssigwasserprofilen abweichen, so dass die Nutzung der Profile kaum zusätzliche Information für die Rekonstruktion liefert. Im zweiten Teil des Rekonstruktionsansatzes wird die Qualität der rekonstruierten Wolkenfelder durch den Vergleich von Parametern des Strahlungstransfers, wie Photonenpfad-Statistiken und Strahlungsgrößen, evaluiert. Dazu wurden sowohl für die surrogaten Wolkenfelder als auch für die rekonstruierten Wolkenfelder dreidimensionale Strahlungstransfersimulationen mit einem Monte-Carlo-Modell durchgeführt. Angenommen wurde hierbei, dass eine bessere Rekonstruktionsqualität durch geringere Abweichungen der betrachteten Strahlungsparameter aus Simulationen mit rekonstruierten und surrogaten Wolkenfeldern gekennzeichnet ist. Bei den Parametern, die die Photonenwege beschreiben, unterstützen lediglich die Abweichungen der geometrischen Photonenweglängen diese These. Weder erlauben die Abweichungen der übrigen Parameter, zum Beispiel der Eindringtiefen, Rückschlüsse auf die lokale Rekonstruktionsqualität der einzelnen Methoden zu ziehen, noch ermöglichen sie die beste Rekonstruktionsmethode zu identifizieren. Auch die Unterschiede der simulierten Reflektanzen können nicht zur Bestimmung der Rekonstruktionsqualität herangezogen werden. Durch Effekte wie horizontale Photonentransporte werden die Zusammenhänge zwischen mikrophysikalischen und optischen Eigenschaften und Reflektanzen der jeweiligen Gittersäule aufgeweicht, und folglich sind keine Rückschlüsse auf die lokale Rekonstruktionsqualität möglich. Um auf entsprechende Effekte einzugehen, wurden für die Analyse Wichtungsfelder unterschiedlicher Komplexität aus Photonenwegeigenschaften generiert, um diese zur Wichtung der Abweichungen der Wolkeneigenschaften zu nutzen. Der Anteil der erklärten Varianz konnte jedoch durch die Nutzung der entsprechenden Wichtungsfelder nicht erhöht werden. Zusätzlich wurden Sensitivitätsstudien hinsichtlich einzelner Vorgaben der Untersuchung durchgeführt. Dazu wurden sowohl der Einfluss der räumlichen Auflösung der Wolkenfelder als auch die Vereinfachung oder Nichtbetrachtung einzelner Modellparameter analysiert. Eine Reduzierung der Auflösung einhergehend mit einem zuverlässigeren Sampling und reduzierten Photonentransport zwischen den Gittersäulen führte zu keinem direkteren Zusammenhang zwischen den Abweichungen der Reflektanzen und den Abweichungen der mikrophysikalischen Eigenschaften. Folglich existiert keine Auflösung, die die Anwendung des Verfahrens ermöglichen würde. Ebenso wurde gezeigt, dass die unzureichende Einbeziehung von Aerosolen bei den Strahlungstransfersimulationen einen Fehler verursachen kann, der in der Größe dem Unterschied der Reflektanzen unzureichender Wolkenfeldrekonstruktionen gleichkommt. Dies ist insbesondere der Fall, wenn die Wolken sich innerhalb der Grenzschicht des Aerosolmodells befinden. Entspechend sollte in solchen Situationen dem verwendeten Aerosolmodell besondere Beachtung geschenkt werden. Hingegen ist der Einfluss des Ansatzes, wie die Bodenreflektion beschrieben wird, eher gering. Dies mag an dem verwendeten Modell mit einer geringen Albedo in Kombination mit optisch dicken Wolken liegen. Zusammenfassend kann festgestellt werden, dass die Unterschiede im Strahlungstransfer nicht zur Abschätzung der Rekonstruktionsqualität der Wolkenfelder herangezogen werden können. Um dem Ziel einer dreidimensionalen Wolkenfeldrekonstruktion näher zu kommen, könnten beim Rekonstruktionsteil Informationen aus zusätzlichen Messungen als Vorgaben genutzt werden. Ebenso könnten Beobachtungsgeometrien, welche die Anwendung tomographischer Methoden erlauben, sowie zusätzliche Wellenlängen zur Validierung der Rekonstruktionsergebnisse verwendet werden.

ABSTRACT Although he was legally blind, Charles R. Knight (1874–1953) established himself as the premier paleontological artist in the early 1900s. When the Field Museum, Chicago, commissioned a series of large paintings to document the evolution of life, Knight was the obvious choice. Knight considered himself an artist guided by science; he researched and illustrated living animals and modern landscapes to better understand and represent extinct life forms within their paleoecosystems. Knight began the process by examining fossil skeletons; he then constructed small models to recreate the animals’ life anatomy and investigate lighting. Once details were finalized, Knight supervised assistants to transfer the study painting to the final mural. The Field Museum mural process, a monumental task of translating science into public art, was accompanied by a synergistic tension between Knight, who wanted full control over his artwork, and the museum’s scientific staff; the correct position of an Eocene whale’s tail—whether uplifted or not—documents a critical example. Although modern scientific understanding has rendered some of Knight’s representations obsolete, the majority of his 28 murals remain on display in the Field Museum’s Evolving Planet exhibit. Museum educators contrast these murals with contemporary paleontological knowledge, thereby demonstrating scientific progress for better public understanding of the nature of science.

Hypopharyngeal carcinoma is uncommon in all head and neck cancers. With a synergistic reaction of each, tobacco consumption and alcohol abuse contribute to the tumorigenesis. The aerodigestive tract epithelium exposure to similar risks causing multiple cancers. Thus, a pan-endoscopic screening offers a practical approach for evaluating second primary esophageal cancer. The common symptoms of hypopharyngeal carcinoma were globus pharyngeus, sore throat, dysphagia, otalgia, neck mass, hoarseness, and dyspnoea. However, approximately 75–80% of patients are initial diagnosed with advanced-stage. Although improvements in therapy, the prognosis is still lacking. In early-stage patients, primary surgical resection and radiotherapy achieved similar survival and locoregional control rates. T1–T2 malignancies with N0–N1 can usually be treated with radiation alone, open surgery, or transoral surgery. In some people, after primary surgery or transoral approaches is often required adjuvant radiotherapy. However, most cases have been in the advanced-stage when screened. Individual therapy programs should be chosen carefully to achieve a balance between swallowing-voice rehabilitation and organ preservation in advanced-stage ones. Meanwhile, reasonable reconstruction of intraoperative defect is essential for a surgeon who seeks satisfied postoperative outcomes. Considerable treatment (surgery or non-surgery) remains the key point of improving the survival rate.

Platelet rich fibrin (PRF) is an autologous biological product which becomes popular day by day and available in a wide variety of fields in medicine. Platelet concentrates which are introduced at the early 90s have evolved over the years. The use such autologous materials have become trendy in recent years to encounter demanding expectations of patients, improve treatment success and maximize patient comfort. Despite its increasing use in dentistry and oral surgery, the most indications and effects are still being discussed. PRF is easily accepted by patients because of its low cost, easy to receive, low donor morbidity, low postoperative complication and infection rate. This biomaterial may be a solution for patients who have strong negative beliefs about the use of allografts and xenografts or who are afraid of complications during the grafting procedure. The objectives of these technologies are to use their synergistic effect to improve the hard and soft tissue regeneration. PRF in oral surgery are used for alveolar bone reconstruction, dental implant surgery, sinus augmentation, socket preservation, osteonecrosis, oroantral fistula closure, struggling with oral ulcers, preventing swelling and edema constitution. This chapter aims to review the clinical applications of platelets in oral surgery and the role of molecular components in tissue healing.