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Real-time computational speed and a high degree of precision are requirements for computer-assisted interventions. Applying a segmentation network to a medical video processing task can introduce significant inter-frame prediction noise. Existing approaches can reduce inconsistencies by including temporal information but often impose requirements on the architecture or dataset. This paper proposes a method to include temporal information in any segmentation model and, thus, a technique to improve video segmentation performance without alterations during training or additional labeling. With Motion-Corrected Moving Average, we refine the exponential moving average between the current and previous predictions. Using optical flow to estimate the movement between consecutive frames, we can shift the prior term in the moving-average calculation to align with the geometry of the current frame. The optical flow calculation does not require the output of the model and can therefore be performed in parallel, leading to no significant runtime penalty for our approach. We evaluate our approach on two publicly available segmentation datasets and two proprietary endoscopic datasets and show improvements over a baseline approach.
Heavy smoke development represents an important challenge for operating physicians during laparoscopic procedures and can potentially affect the success of an intervention due to reduced visibility and orientation. Reliable and accurate recognition of smoke is therefore a prerequisite for the use of downstream systems such as automated smoke evacuation systems. Current approaches distinguish between non-smoked and smoked frames but often ignore the temporal context inherent in endoscopic video data. In this work, we therefore present a method that utilizes the pixel-wise displacement from randomly sampled images to the preceding frames determined using the optical flow algorithm by providing the transformed magnitude of the displacement as an additional input to the network. Further, we incorporate the temporal context at evaluation time by applying an exponential moving average on the estimated class probabilities of the model output to obtain more stable and robust results over time. We evaluate our method on two convolutional-based and one state-of-the-art transformer architecture and show improvements in the classification results over a baseline approach, regardless of the network used.
Seit mehr als 25 Jahren ist der Workshop "Bildverarbeitung für die Medizin" als erfolgreiche Veranstaltung etabliert. Ziel ist auch 2024 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespräche zwischen Wissenschaftlern, Industrie und Anwendern. Die Beiträge dieses Bandes - viele davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere die Bildgebung und -akquisition, Segmentierung und Analyse, Visualisierung und Animation, computerunterstützte Diagnose sowie bildgestützte Therapieplanung und Therapie. Hierbei kommen Methoden des maschinelles Lernens, der biomechanischen Modellierung sowie der Validierung und Qualitätssicherung zum Einsatz.
In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were “instrument segmentation”, “instrument tracking”, “surgical tool segmentation”, and “surgical tool tracking”, resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments.
The utilization of virtual reality (VR) technology has shown promise in various therapeutic applications, particularly in exposure therapy
for reducing fear of certain situations objects or activities, e.g. fear of height, or negative evaluation of others in social situations. VR has been shown to yield positive outcomes in follow-up studies, and provides a safe and ecological therapeutic environment for therapists and their patients. This paper presents a collaborative
effort to develop a VR speech therapy system which simulates a virtual audience for users to practice their public speaking skills. We describe a novel web-based graphica user interface that enables
therapists to manage the therapy session using a simple timeline. Lastly, we present the results from a qualitative study with therapists and teachers with functional dysphonia, which highlight the potential of such an application to support and augment the therapists’ work and the remaining challenges regarding the design of natural interactions, agent behaviours and scenario customisation for patients.
Wie können Pflege und Gesundheitswesen so digitalisiert werden, dass alle davon profitieren? Dieser Frage widmen sich Expert*innen aus den Bereichen Medizin, Pflege und Therapie. Sie präsentieren Ergebnisse, die im Kontext der Veranstaltung »Digitalisierung im Gesundheitswesen – Gehen Sie mit uns in eine neue Zukunft« an der Ostbayerischen Technischen Hochschule Regensburg im Juli 2022 entstanden. Im Mittelpunkt steht dabei die Projektreihe »DeinHaus 4.0«. Daneben bespielen die Beiträge aber auch die Themen digitale Versorgungsanwendungen in Pflege und Gesundheit, Akzeptanz und Nutzung von sozio-assistiven Technologien in der Pflege sowie digitalisierte Logopädie bzw. Physiotherapie.
BACKGROUND: Thrombosis remains a critical complication during venovenous extracorporeal membrane oxygenation (VV ECMO). The involvement of neutrophil extracellular traps (NETs) in thrombogenesis has to be discussed. The aim was to verify NETs in the form of cell-free DNA (cfDNA) in the plasma of patients during ECMO.
METHODS: A fluorescent DNA-binding dye (QuantifFluor®, Promega) was used to detect cell-free DNA in plasma samples. cfDNA concentrations from volunteers (n = 21) and patients (n = 9) were compared and correlated with clinical/technical data before/during support, ECMO end and time of a system exchange.
RESULTS: Before ECMO, patients with a median (IQR) age of 59 (51/63) years, SOFA score of 11 (10/15), and ECMO run time of 9.0 (7.0/19.5) days presented significantly higher levels of cfDNA compared to volunteers (6.4 (5.8/7.9) ng/μL vs. 5.9 (5.4/6.3) ng/μL; p = 0.044). Within 2 days after ECMO start, cfDNA, inflammatory, and hemolysis parameters remained unchanged, while platelets decreased (p = 0.005). After ECMO removal at the end of therapy, cfDNA, inflammation, and coagulation data (except antithrombin III) remained unchanged. The renewal of a system resulted in known alterations in fibrinogen, d-dimers, and platelets, while cfDNA remained unchanged.
CONCLUSION: Detection of cfDNA in plasma of ECMO patients was not an indicator of acute and circuit-induced thrombogenesis.
Menschen mit Aphasie erleben erhebliche Einbußen in sozialer Teilhabe und Lebensqualität. Peer-to-Peer-Unterstützung durch Selbsthilfeangebote oder Peer-Befriending-Maßnahmen kann sich positiv auf Partizipation und psychisches Wohlbefinden auswirken. Mit dem Projekt shalk konnte gezeigt werden, dass von Betroffenen geleitete Selbsthilfegruppen maßgeblich zu Selbstwerterleben und verbesserter Lebensqualität der Leitungspersonen und der Gruppenteilnehmenden beitragen können. Um einen Austausch zwischen Betroffenen auch jenseits des Gruppensettings zu ermöglichen, können digitale Medien genutzt werden. Im Projekt PeerPAL wird ein für Menschen mit Aphasie angepasstes digitales soziales Netzwerk (Smartphone-App) zur virtuellen Vernetzung und persönlichen Begegnung entwickelt und evaluiert. Erste Daten weisen darauf hin, dass die Betroffenen die App nutzen können und mit Design und Funktionen zufrieden sind. Auswirkungen auf die Lebensqualität werden aktuell untersucht. Sprachtherapeut:innen nehmen in der Peer-to-Peer-Unterstützung insofern eine zentrale Rolle ein, als dass sie Betroffene in entsprechende Angebote einführen und sie mittels abgestufter Begleitung an die eigenständige Nutzung heranführen.
Aufgrund der steigenden Lebenserwartung und dem damit einhergehenden demographischen Wandel wird der Bedarf an Rehabilitations-Behandlungen in absehbarer Zukunft stark ansteigen. Ein Beispiel für diesen Trend ist die physiotherapeutische Behandlung nach Erhalt einer Knie-Totalendoprothese (Knie-TEP). So gehen Modellrechnungen basierend auf dem Bevölkerungswachstum und der bisherigen Prävalenz von Knie-TEPs davon aus, dass die Anzahl an durchgeführten Eingriffen in einkommensstarken Ländern wie Deutschland weiter zunehmen wird. Weiterhin stoßen traditionelle Rehabilitationsverfahren, gerade in strukturschwachen Regionen, schon heute an ihre Grenzen. Deutlich zu sehen war das während den Hochphasen der aktuellen Covid-19-Pandemie, als der Kontakt zwischen Therapeut*in und Patient*in flächendeckend eingeschränkt war. Eine erhöhte Nachfrage nach neuartigen Reha-Angeboten ist die logische Konsequenz. Innovative Konzepte sind daher dringend notwendig, um die daraus resultierenden technischen, sozialen und ökonomischen Herausforderungen zu bewältigen.
Der Beitrag untersucht den Diskurs um Freiheit während der Coronakrise, indem er mediale Aushandlungen von Freiheit, Selbstbestimmung und Corona in der deutschen Tageszeitungsberichterstattung im Frühling des Jahres 2020 beleuchtet. Methodisch orientiert er sich dabei an der Deutungsmusteranalyse und nutzt inhaltsanalytische Codierungsverfahren. Freiheit erweist sich bereits in einer frühen Phase der Pandemie als stark thematisiert und diskursiv umkämpft. Grundrechte und mehrere Bereiche des persönlichen Lebens werden referenziert und Auswirkungen der Coronakrise auf jene unterschiedlich beschrieben. Die analysierten Deutungsmuster beziehen sich u. a. auf die allgemeine Handlungsfreiheit im Zuge einer pandemiebedingten Zäsur, auf Beschränkungen des Reisens, auf die Möglichkeit körperlicher Unversehrtheit, auf die Bedingungen von Versammlungs- sowie Meinungs- und Pressefreiheit. Der Beitrag rekonstruiert über die mediale Auseinandersetzung Folgen und Nebenfolgen, die mit der Krise und den Strategien der Pandemiebekämpfung einhergingen – sie tragen angesichts eines neuen Potenzials von Überwachung und staatlicher Kontrolle auch das Risiko in sich, Freiheitsrechte in (digitalen) Gesellschaften prekär werden zu lassen. Insgesamt zeigt sich der Diskurs als differenzierte sowie detaillierte Auseinandersetzung mit Freiheit in einer außergewöhnlichen Situation.
Die Behandlung von Menschen mit demenziellen Erkrankungen erfordert wirksame Maßnahmen zur nachhaltigen Unterstützung der Betroffenen und ihrer Angehörigen. In Pflege und Therapie gewinnt die biografieorientierte Arbeit an Bedeutung, um die Lebensqualität und die durch dieErkrankung beeinträchtigten kognitiven Fähigkeiten so lange wie möglich zuerhalten und möglichst zu verbessern. In dem systematischen Review wurdenaktuelle Evidenzen aus zehn randomisiert-kontrollierten Studien untersucht, die sich mit der Frage nach der Effektivität biografieorientierter Maßnahmen beschäftigen, und praxisorientierte Schlussfolgerungen für logopädische Therapien
abgeleitet.
BACKGROUND:
Tracheobronchial mucus plays a crucial role in pulmonary function by providing protection against inhaled pathogens. Due to its composition of water, mucins, and other biomolecules, it has a complex viscoelastic rheological behavior. This interplay of both viscous and elastic properties has not been fully described yet. In this study, we characterize the rheology of human mucus using oscillatory and transient tests. Based on the transient tests, we describe the material behavior of mucus under stress and strain loading by mathematical models.
METHODS:
Mucus samples were collected from clinically used endotracheal tubes. For rheological characterization, oscillatory amplitude-sweep and frequency-sweep tests, and transient creep-recovery and stress-relaxation tests were performed. The results of the transient test were approximated using the Burgers model, the Weibull distribution, and the six-element Maxwell model. The three-dimensional microstructure of the tracheobronchial mucus was visualized using scanning electron microscope imaging.
RESULTS:
Amplitude-sweep tests showed storage moduli ranging from 0.1 Pa to 10000 Pa and a median critical strain of 4 %. In frequency-sweep tests, storage and loss moduli increased with frequency, with the median of the storage modulus ranging from 10 Pa to 30 Pa, and the median of the loss modulus from 5 Pa to 14 Pa. The Burgers model approximates the viscoelastic behavior of tracheobronchial mucus during a constant load of stress appropriately (R2 of 0.99), and the Weibull distribution is suitable to predict the recovery of the sample after the removal of this stress (R2 of 0.99). The approximation of the stress-relaxation test data by a six-element Maxwell model shows a larger fit error (R2 of 0.91).
CONCLUSIONS:
This study provides a detailed description of all process steps of characterizing the rheology of tracheobronchial mucus, including sample collection, microstructure visualization, and rheological investigation. Based on this characterization, we provide mathematical models of the rheological behavior of tracheobronchial mucus. These can now be used to simulate mucus flow in the respiratory system through numerical approaches.
DeinHaus 4.0 Oberbayern
(2023)
Onlinetherapie für Menschen mit Aphasie - Tipps und Hinweise zur Anwendung im therapeutischen Alltag
(2023)
9x Ofra: Technikunterstütztes Wohnen als Beitrag zur Verbesserung der kommunalen Daseinsvorsorge
(2023)
Für Fußballer:innen stellen muskuläre Verletzungen der unteren Extremitäten ein großes Problem dar. Ein Beispiel hierfür liefert die Nationalmannschaftsstürmerin Alexandra Popp, die aufgrund muskulärer Probleme das EM-Finale 2022 in Wembley kurzfristig verpasste. Oftmals stehen gerade hohe Anspannungssituationen in zeitlichem Zusammenhang mit Verletzungen, der Einfluss der psychischen Beanspruchung auf die biomechanischen Belastungen wird jedoch meist nur wenig beachtet.
To avoid dislocation of the shoulder joint after reverse total shoulder arthroplasty, it is important to achieve sufficient shoulder stability when placing the implant components during surgery. One parameter for assessing shoulder stability can be shoulder stiffness. The aim of this research was to develop a temporary reverse shoulder implant prototype that would allow intraoperative measurement of shoulder stiffness while varying the position of the implant components. Joint angle and torque measurement techniques were developed to determine shoulder stiffness. Hall sensors were used to measure the joint angles by converting the magnetic flux densities into angles. The accuracy of the joint angle measurements was tested using a test bench. Torques were determined by using thin-film pressure sensors. Various mechanical mechanisms for variable positioning of the implant components were integrated into the prototype. The results of the joint angle measurements showed measurement errors of less than 5° in a deflection range of ±15° adduction/abduction combined with ±45° flexion/extension. The proposed design provides a first approach for intra-operative assessment of shoulder stiffness. The findings can be used as a technological basis for further developments.
Background:
People with aphasia (PWA) often suffer from reduced participation and quality of life. Nevertheless, there are currently only a few specific interventions that respond to this problem. Participation and quality of life could be increased by interacting with peers who have similar experiences. Digital social networks could stimulate an autonomous interaction. However, digital social networks need to be adapted to the specific needs of PWA. Therefore, a participatory, agile process involving the target group should be chosen to develop such a olution, i.e., an app. The research project consists of a total of three phases. In the first phase—app development—the app was developed and programmed including the target group. In the second phase—app testing—the usability and user-friendliness of the app were evaluated with four PWA. In the third phase—feasibility and preliminary effcacy—that will be described in the article, the impact of the app on PWA will be evaluated.
Aims:
The overarching aim of our study is to provide preliminary effcacy of the intervention. Digital social interaction with other PWA can lead to increased social integration. In addition to digital interaction, personal encounters between PWA should be encouraged. As a result, we expect an improvement in quality of life of PWA. Additionally, we focus on identification of the most appropriate measurements to discover changes associated with the intervention.
Methods:
The evaluation, which is described in this paper, takes place in a pre-test - post-test design with a total of n = 48 PWA. Participants will be recruited in regional clusters to facilitate face-to-face meetings. Half of the participants will be assigned to the delayed intervention group and the other half to the immediate intervention group. Participants in the delayed intervention group will go through a 3-month waiting period before using the app, while the participants of the immediate intervention group will start using the app for 3 months right away. Inclusion criteria are the presence of chronic aphasia (at least 6 months) and possession of a smartphone with internet access. Questionnaires on quality of life (SAQOL-39, GHQ-12), depression (GDS, DISCs), communicative participation (CPIB), and social support (F-SozU) will be conducted at inclusion (t0), after 3 months of app use (t1), and after another 3 months for follow-up (t2). Participants in the delayed intervention group will be assessed twice before the intervention, before the 3-month waiting period (t0a) and after the waiting period (t0b). In addition to the quantitative measures, interviews will take place with 6 to 8 selected participants after 3 months of app use. Responses will be analysed using Thematic Analysis.
Discussion:
The app will be the first social network tool that is systematically developed with PWA. Initial indications from the first phases are that the app can be used by PWA, so that the evaluation of this app version can take place in the third phase. Results of this study can provide an initial indication of whether social network support is a suitable intervention. Findings will help provide information on the feasibility of digital connectivity for PWA. Preliminary findings on its impact on the participation and quality of life of PWA could be made available.
Ziel der Studie:
Ziel der Studie ist die Messung des Stands der Digitalisierung und die mit einer Anbindung an die Telematikinfrastruktur verbundenen Chancen und Herausforderungen für Rehabilitationseinrichtungen.
Methodik:
Teilstandardisierte Online-Befragung bei Trägern von Rehabilitationseinrichtungen in Bayern (n=33). Der Fragebogen mit 36 Fragen beinhaltet eine leicht veränderte Skala auf Basis des „Electronic Medical Record Adoption Model (EMRAM)“.
Ergebnisse:
Der Digitalisierungsgrad wurde in 70 Prozent der Rehabilitationseinrichtungen mit Stufe 0 angegeben (Stufenmodell bis 7). Die Übermittlung patientenbezogener Daten (Eingang und Ausgang) erfolgt häufig analog, wohingegen die Verarbeitung innerhalb der Einrichtung in vielen Fällen bereits überwiegend digital ist. Beim Anschluss an die Telematikinfrastruktur wird hoher Aufwand bei der Installation, aber auch der Schulung des Personals und der Anpassung der Arbeitsorganisation gesehen.
Schlussfolgerung:
Durch Änderung der gesetzlich-finanziellen Lage in Deutschland eröffnen sich für Rehabilitationseinrichtungen neue Möglichkeiten einer verstärkten Digitalisierung. Hürden hängen mit Anforderungen an IT-Sicherheit, Schulung des Personals und sowie dem ebenfalls geringen Digitalisierungsstand bei Krankenhäusern und Ärzt*innen sowie Patient*innen zusammen, die eine digitale Datenübermittlung erschweren.
Seit mehr als 25 Jahren ist der Workshop "Bildverarbeitung für die Medizin" als erfolgreiche Veranstaltung etabliert. Ziel ist auch 2023 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespräche zwischen Wissenschaftlern, Industrie und Anwendern. Die Beiträge dieses Bandes - viele davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere die Bildgebung und -akquisition, Segmentierung und Analyse, Visualisierung und Animation, computerunterstützte Diagnose sowie bildgestützte Therapieplanung und Therapie. Hierbei kommen Methoden des maschinelles Lernens, der biomechanischen Modellierung sowie der Validierung und Qualitätssicherung zum Einsatz.
Older adults in long-term care homes are at high risk of experiencing
reduced quality of life (QoL) and depression. Technology-assisted biography work can have a positive impact on QoL and mood, but there is little research on its use with this target group. The purpose of this paper is to examine the effect of tablet-based biography work conducted by volunteers on the QoL of residents and volunteers. A pretest-posttest control group design with an intervention period of 3 months and a 3-month follow-up was used. Results show a significant increase in participation for volunteers and residents after
the intervention, which is stable for residents until follow-up. Volunteers also show significant improvement in mental QoL immediately after the intervention. There were no significant effects for life satisfaction, self-esteem, or depression. No significant changes were found for the control group. Digitally conducted tablet-based biography work appears to have effects on QoL-associated outcomes.
Menschen mit einer erworbenen Sprachstörung, Aphasie, erleben aufgrund ihrer Kommunikationseinschränkungen und der damit einhergehenden reduzierten Teilhabe eine verminderte Lebensqualität. Aphasie-Selbsthilfegruppen können Inklusion und Selbstwerterleben der Betroffenen besonders dann fördern, wenn sie von betroffenen Personen selbst geleitet werden. In dem hier vorgestellten Forschungsprojekt Selbsthilfegruppenarbeit bei Aphasie zur Steigerung der Lebensqualität und Kompetenz (shalk) wurde untersucht, wie von Aphasie betroffene Menschen auf die Übernahme einer Gruppenleitung vorbereitet und bei der Umsetzung begleitet werden können, um die Lebensqualität der betroffenen Leitungspersonen und auch der Gruppenteilnehmenden zu steigern.
Aims
VA is an endoscopic finding of celiac disease (CD), which can easily be missed if pretest probability is low. In this study, we aimed to develop an artificial intelligence (AI) algorithm for the detection of villous atrophy on endoscopic images.
Methods
858 images from 182 patients with VA and 846 images from 323 patients with normal duodenal mucosa were used for training and internal validation of an AI algorithm (ResNet18). A separate dataset was used for external validation, as well as determination of detection performance of experts, trainees and trainees with AI support. According to the AI consultation distribution, images were stratified into “easy” and “difficult”.
Results
Internal validation showed 82%, 85% and 84% for sensitivity, specificity and accuracy. External validation showed 90%, 76% and 84%. The algorithm was significantly more sensitive and accurate than trainees, trainees with AI support and experts in endoscopy. AI support in trainees was associated with significantly improved performance. While all endoscopists showed significantly lower detection for “difficult” images, AI performance remained stable.
Conclusions
The algorithm outperformed trainees and experts in sensitivity and accuracy for VA detection. The significant improvement with AI support suggests a potential clinical benefit. Stable performance of the algorithm in “easy” and “difficult” test images may indicate an advantage in macroscopically challenging cases.
Aims
Evaluation of the add-on effect an artificial intelligence (AI) based clinical decision support system has on the performance of endoscopists with different degrees of expertise in the field of Barrett's esophagus (BE) and Barrett's esophagus-related neoplasia (BERN).
Methods
The support system is based on a multi-task deep learning model trained to solve a segmentation and several classification tasks. The training approach represents an extension of the ECMT semi-supervised learning algorithm. The complete system evaluates a decision tree between estimated motion, classification, segmentation, and temporal constraints, to decide when and how the prediction is highlighted to the observer. In our current study, ninety-six video cases of patients with BE and BERN were prospectively collected and assessed by Barrett's specialists and non-specialists. All video cases were evaluated twice – with and without AI assistance. The order of appearance, either with or without AI support, was assigned randomly. Participants were asked to detect and characterize regions of dysplasia or early neoplasia within the video sequences.
Results
Standalone sensitivity, specificity, and accuracy of the AI system were 92.16%, 68.89%, and 81.25%, respectively. Mean sensitivity, specificity, and accuracy of expert endoscopists without AI support were 83,33%, 58,20%, and 71,48 %, respectively. Gastroenterologists without Barrett's expertise but with AI support had a comparable performance with a mean sensitivity, specificity, and accuracy of 76,63%, 65,35%, and 71,36%, respectively.
Conclusions
Non-Barrett's experts with AI support had a similar performance as experts in a video-based study.
Aims
AI has proven great potential in assisting endoscopists in diagnostics, however its role in therapeutic endoscopy remains unclear. Endoscopic submucosal dissection (ESD) is a technically demanding intervention with a slow learning curve and relevant risks like bleeding and perforation. Therefore, we aimed to develop an algorithm for the real-time detection and delineation of relevant structures during third-space endoscopy.
Methods
5470 still images from 59 full length videos (47 ESD, 12 POEM) were annotated. 179681 additional unlabeled images were added to the training dataset. Consequently, a DeepLabv3+ neural network architecture was trained with the ECMT semi-supervised algorithm (under review elsewhere). Evaluation of vessel detection was performed on a dataset of 101 standardized video clips from 15 separate third-space endoscopy videos with 200 predefined blood vessels.
Results
Internal validation yielded an overall mean Dice score of 85% (68% for blood vessels, 86% for submucosal layer, 88% for muscle layer). On the video test data, the overall vessel detection rate (VDR) was 94% (96% for ESD, 74% for POEM). The median overall vessel detection time (VDT) was 0.32 sec (0.3 sec for ESD, 0.62 sec for POEM).
Conclusions
Evaluation of the developed algorithm on a video test dataset showed high VDR and quick VDT, especially for ESD. Further research will focus on a possible clinical benefit of the AI application for VDR and VDT during third-space endoscopy.
In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images. Especially the determination of the position and type of the instruments is of great interest here. Current work involves both spatial and temporal information with the idea, that the prediction of movement of surgical tools over time may improve the quality of final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify datasets used for method development and evaluation, as well as quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images. The paper focuses on methods that work purely visually without attached markers of any kind on the instruments, taking into account both single-frame segmentation approaches as well as those involving temporal information. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing available potential for future developments. The publications considered were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were "instrument segmentation", "instrument tracking", "surgical tool segmentation", and "surgical tool tracking" and result in 408 articles published between 2015 and 2022 from which 109 were included using systematic selection criteria.
Surgical Smoke is generated during the cauterization of tissue with high-frequency (HF) devices and consists of 95% water vapor and 5% cellular debris. When the coagulation tweezers, which are supplied with HF voltage by the HF device, touch tissue, the electric circuit is closed, and smoke is generated by the heat. In-vivo investigations are performed during tracheotomies where surgical smoke is produced during coagulation of tissue. Furthermore, in-vitro parametric studies to investigate the particle number and size distribution and the spatial distribution of surgical smoke with laser light sheet technique are conducted. With higher power of the HF device, the particles generated are larger in size and the total number of particles generated is also higher. Adding artificial saliva to the tissue shows even higher particle counts. The study by laser light sheet also confirms this. The resulting characteristic size distribution, which may include viruses and bacterial components, confirms considering the risk arising from surgical smoke. Furthermore, the experiments will provide the database for further numerical investigations.
High Spatial Resolution Tomo-PIV of the Trachea Focussing on the Physiological Breathing Cycle
(2023)
Investigations of complex patient-specific flow in the nasopharynx requires high resolution numerical calculations validated by reliable experiments. When building the validation base and the benchmark of computational fluid dynamics, an experimental setup of the nasal airways was developed. The applied optical measurement technique of tomo-PIV supplies information on the governing flow field in three dimensions.
This paper presents tomo-PIV measurements of the highly complex patient-specific geometry of the human trachea. A computertomographic scan of a person’s head builds the basis of the experimental silicone model of the nasal airways. An optimised approach for precise refractive index matching avoids optical distortions even in highly complex non-free-of-sight 3D geometries. A linear-motor-driven pump generates breathing scenarios, based on measured breathing cycles. Adjusting of the CCD cameras‘ double-frame-rate PIV-Δt enables the detailed analysis of flow structures during different cycle phases. Merging regions of interest enables high spatial resolution acquisition of the flow field.
Für Mutter und Kind konnte das Risiko der Geburt durch die Weiterentwicklung der Medizin drastisch reduziert werden. Doch wie ist es um das Wohl derer bestellt, die die Gebärende unterstützen? Eine Studie der Ostbayerischen Technischen Hochschule Regensburg hat sich mit den muskuloskelettalen Beschwerden von Geburtshelfer:innen auseinandergesetzt
Gesundheit und Soziales
(2023)
Osteoporosis is a common disease of old age. However, in many cases, it can be very well prevented and counteracted with physical activity, especially high-impact exercises. Wearables have the potential to provide data that can help with continuous monitoring of patients during therapy phases or preventive exercise programs in everyday life. This study aimed to determine the accuracy and reliability of measured acceleration data at different body positions compared to accelerations at the pelvis during different jumping exercises. Accelerations at the hips have been investigated in previous studies with regard to osteoporosis prevention. Data were collected using an IMU-based motion capture system (Xsens) consisting of 17 sensors. Forty-nine subjects were included in this study. The analysis shows the correlation between impacts and the corresponding drop height, which are dependent on the respective exercise. Very high correlations (0.83–0.94) were found between accelerations at the pelvis and the other measured segments at the upper body. The foot sensors provided very weak correlations (0.20–0.27). Accelerations measured at the pelvis during jumping exercises can be tracked very well on the upper body and upper extremities, including locations where smart devices are typically worn, which gives possibilities for remote and continuous monitoring of programs.
Das Virus SARS-CoV-2 und die dadurch ausgelöste Coronapandemie haben die Gesellschaft in einen Krisenmodus versetzt: Die Coronapandemie hat tiefgreifenden Einfluss auf den Alltag von Subjekten in allen Lebenslagen genommen, gesellschaftliche Bedingungen verändert und institutionelle Veränderungen angestoßen. Ob das Tragen eines Mund-Nasen-Schutzes, die virtuelle Kommunikation als neuer Standard in Arbeitsumgebungen oder Regelungen zu Impfungen und öffentlichem Gesundheitsschutz – gesellschaftliche Praktiken und Diskurse haben sich verändert sowie Wissensregime etabliert, die einer genaueren multidisziplinären Analyse würdig sind. Der Band versammelt Beiträge zu Bereichen, die von einem krisenbedingten Wandel betroffen sind: Alter, Bildung, Emotion, Freiheit, Geschlecht, Gesundheit, Digitalisierung, Körper, Medizin und Versorgung sowie Sorgebeziehungen.