PDEs for tensor image processing

Methods based on partial differential equations (PDEs) belong to those image processing techniques that can be extended in a particularly elegant way to tensor fields. In this survey paper the most important PDEs for discontinuity-preserving denoising of tensor fields are reviewed such that the underlying design principles becomes evident. We consider isotropic and anisotropic diffusion filters and their corresponding variational methods, mean curvature motion, and selfsnakes. These filters preserve positive semidefiniteness of any positive semidefinite initial tensor field. Finally we discuss geodesic active contours for segmenting tensor fields. Experiments are presented that illustrate the behaviour of all these methods

Continuous observations of the surface energy budget and meteorology over the Arctic sea ice during MOSAiC

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was a yearlong expedition supported by the icebreaker R/V Polarstern, following the Transpolar Drift from October 2019 to October 2020. The campaign documented an annual cycle of physical, biological, and chemical processes impacting the atmosphere-ice-ocean system. Of central importance were measurements of the thermodynamic and dynamic evolution of the sea ice. A multi-agency international team led by the University of Colorado/CIRES and NOAA-PSL observed meteorology and surface-atmosphere energy exchanges, including radiation; turbulent momentum flux; turbulent latent and sensible heat flux; and snow conductive flux. There were four stations on the ice, a 10 m micrometeorological tower paired with a 23/30 m mast and radiation station and three autonomous Atmospheric Surface Flux Stations. Collectively, the four stations acquired ~928 days of data. This manuscript documents the acquisition and post-processing of those measurements and provides a guide for researchers to access and use the data products

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Overview of the MOSAiC expedition—Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic

Patient-specific planning for radio-frequency ablation of tumors in the presence of uncertainty

Die Hochfrequenzstrom Ablation (RF Ablation) ist eine vielversprechende minimalinvasive Therapie für Tumore und Metastasen in der Leber. Dabei induziert ein nadelförmiger Applikator, der perkutan in die Läsion eingeführt wird, einen lokalen Stromfluss der durch den Ohmschen Widerstand des Gewebes zu seiner Erwärmung und Zerstörung führt. Damit die RF Ablation einen ähnlichen klinischen Stellenwert einnehmen kann, wie die chirurgische Resektion, muss eine vollständige Ablation vergleichbar der R0 Resektion erreicht werden. Hier liefern die Patienten-individuelle Modellierung und numerische Simulation der bio-physikalischen Prozesse einen wertvollen Beitrag zur Therapieplanung, weil sie eine Abschätzung des Therapieerfolges und eine Optimierung der Therapieparameter ermöglichen. In diesem Beitrag wird ein mathematisches Modell mit partiellen Differentialgleichungen (PDEs) für die Patienten-individuelle Simulation der RF Ablation diskutiert. Ein Schwerpunkt liegt auf der Berücksichtigung von Unsicherheiten in den Materialeigenschaften, den zugrunde liegenden Bilddaten und den Ergebnissen der Simulationen. Ein stochastisches PDE Modell wird diskutiert, das eine Analyse der Sensitivität der Simulationsergebnisse unter Schwankungen in den Materialeigenschaften erlaubt. Schließlich wird eine Methode zur schnellen Abschätzung der Gewebezerstörung gezeigt, die auf einer Trennung von Patienten unspezifischen Vorberechnungen und Patienten individuellen Berechnungen beruht, und somit zu einer interaktiven Echtzeit-Simulation führt

Toward focused ultrasound liver surgery under free breathing

Focused ultrasound surgery is an outstanding novel technique for cancer treatment because it is completely noninvasive with the potential for complete and controlled local tumor destruction. Because focused ultrasound surgery is applied from outside of the patient's body, imaging such as ultrasound or magnetic resonance imaging is required to plan and monitor the intervention. For the treatment of liver tumors, several complexities have to be taken into account, including accessibility of the target and protection of structures at risk. To allow for safe and efficient treatment under free respiration, in which the liver moves significantly, both planning and execution have to be performed specifically according to the patient's individual breathing. This article reviews the state of the art of liver applications, the tremendous challenges of this field, and approaches to overcome these challenges. This includes modeling of the patient-individual breathing cycle, detection of and adaptation to the actual breathing, and simulation and monitoring of the therapy

Radiofrequency ablation planning beyond simulation

It is a challenging task to plan a radiofrequency (RF) ablation therapy to achieve the best outcome of the treatment and avoid recurrences at the same time. A patient specific simulation in advance that takes the cooling effect of blood vessels into account is a helpful tool for radiologists, but this needs a very high accuracy and thus high computational costs. In this work, we present various methods, which improve and extend the planning of an RF ablation procedure. First, we discuss two extensions of the simulation model to obtain a higher accuracy, including the vaporization of the water in the tissue and identifying the model parameters and to analyze their uncertainty. Furthermore, we discuss an extension of the planning procedure namely the optimization of the probe placement, which optimizes the overlap of the tumor area with the estimated coagulation in order to avoid recurrences. Since the optimization is constrained by the model, we have to take into account the uncertainties in the model parameters for the optimization as well. Finally, applications of our methods to a real RF ablation case are presented