VOLT: a novel open-source pipeline for automatic segmentation of endolymphatic space in inner ear MRI

BACKGROUND Objective and volumetric quantification is a necessary step in the assessment and comparison of endolymphatic hydrops (ELH) results. Here, we introduce a novel tool for automatic volumetric segmentation of the endolymphatic space (ELS) for ELH detection in delayed intravenous gadolinium-enhanced magnetic resonance imaging of inner ear (iMRI) data. METHODS The core component is a novel algorithm based on Volumetric Local Thresholding (VOLT). The study included three different data sets: a real-world data set (D1) to develop the novel ELH detection algorithm and two validating data sets, one artificial (D2) and one entirely unseen prospective real-world data set (D3). D1 included 210 inner ears of 105 patients (50 male; mean age 50.4 ± 17.1 years), and D3 included 20 inner ears of 10 patients (5 male; mean age 46.8 ± 14.4 years) with episodic vertigo attacks of different etiology. D1 and D3 did not differ significantly concerning age, gender, the grade of ELH, or data quality. As an artificial data set, D2 provided a known ground truth and consisted of an 8-bit cuboid volume using the same voxel-size and grid as real-world data with different sized cylindrical and cuboid-shaped cutouts (signal) whose grayscale values matched the real-world data set D1 (mean 68.7 ± 7.8; range 48.9-92.8). The evaluation included segmentation accuracy using the Sørensen-Dice overlap coefficient and segmentation precision by comparing the volume of the ELS. RESULTS VOLT resulted in a high level of performance and accuracy in comparison with the respective gold standard. In the case of the artificial data set, VOLT outperformed the gold standard in higher noise levels. Data processing steps are fully automated and run without further user input in less than 60 s. ELS volume measured by automatic segmentation correlated significantly with the clinical grading of the ELS (p < 0.01). CONCLUSION VOLT enables an open-source reproducible, reliable, and automatic volumetric quantification of the inner ears' fluid space using MR volumetric assessment of endolymphatic hydrops. This tool constitutes an important step towards comparable and systematic big data analyses of the ELS in patients with the frequent syndrome of episodic vertigo attacks. A generic version of our three-dimensional thresholding algorithm has been made available to the scientific community via GitHub as an ImageJ-plugin

Platform to Assist Medical Experts in Training, Application, and Control of Machine Learning Models Using Patient Data from a Clinical Information System

In recent years, clinical data scientists achieved major breakthroughs advancing machine learning models for the medical domain, which have great potential assisting medical experts. Machine learning models can be leveraged to assist medical experts in tasks such as analyzing and diagnosing patient data, for example, from computed tomography scans. However, it is a challenge to translate the latest advancements in academic research fields such as computer sciences and physics into clinical practice. For this purpose, clinical data scientists and medical experts need to closely collaborate. This thesis tackles challenges of accessibility and usability of state-of-the-art machine learning models as well as designing a scalable computing architecture. Hence, conceptual ideas of possible strategies, as well as a prototype of such a machine learning platform, are presented. A systematic literature review was conducted on the current approaches to create medical machine learning platforms, the management of machine learning models, and the version management of large data sets. Afterward, the functional and nonfunctional requirements of the new machine learning platform were elicited as part of the requirements analysis. Two streamlined workflows for clinical data scientists and medical experts were derived from the requirement analysis. The workflow for the clinical data scientists includes steps to define, train, and share machine learning methods, including pre- and postprocessing modules, and management of data sets. Medical experts are able to analyze patient data using pre-defined machine learning methods. Building on the result of these analyses, the architecture of the platform was derived. The architecture consists of a scalable infrastructure stack, a lightweight and easy-to-use web interface, as well as a backend component to provide the required functionalities. The final design decisions solve the issue of efficiently standardizing, parallelizing, and applying machine learning workflows within a scalable computing infrastructure. The proposed platform was evaluated with 22 participants, consisting of clinical data scientists (N=12) and medical experts (N=10). Both groups were asked to rate specific workflows of the platform, as well as the platform as a whole, and to provide additional ideas and feedback. 92% of the medical experts and 90% of the clinical data scientists rated their overall impression of the platform as very good. Furthermore, medical experts and clinical data scientists strongly agreed that the platform facilitates method development and collaborations with 92% and 90%, respectively. The conducted expert survey suggests that the here proposed platform could be used to develop, optimize, and apply machine learning methods in the medical domain and beyond, thereby easing the collaboration between medical experts and clinical data scientists

IE-Vnet: deep learning-based segmentation of the inner ear's total fluid space

Background In-vivo MR-based high-resolution volumetric quantification methods of the endolymphatic hydrops (ELH) are highly dependent on a reliable segmentation of the inner ear's total fluid space (TFS). This study aimed to develop a novel open-source inner ear TFS segmentation approach using a dedicated deep learning (DL) model. Methods The model was based on a V-Net architecture (IE-Vnet) and a multivariate (MR scans: T1, T2, FLAIR, SPACE) training dataset (D1, 179 consecutive patients with peripheral vestibulocochlear syndromes). Ground-truth TFS masks were generated in a semi-manual, atlas-assisted approach. IE-Vnet model segmentation performance, generalizability, and robustness to domain shift were evaluated on four heterogenous test datasets (D2-D5, n = 4 × 20 ears). Results The IE-Vnet model predicted TFS masks with consistently high congruence to the ground-truth in all test datasets (Dice overlap coefficient: 0.9 ± 0.02, Hausdorff maximum surface distance: 0.93 ± 0.71 mm, mean surface distance: 0.022 ± 0.005 mm) without significant difference concerning side (two-sided Wilcoxon signed-rank test, p>0.05), or dataset (Kruskal-Wallis test, p>0.05; post-hoc Mann-Whitney U, FDR-corrected, all p>0.2). Prediction took 0.2 s, and was 2,000 times faster than a state-of-the-art atlas-based segmentation method. Conclusion IE-Vnet TFS segmentation demonstrated high accuracy, robustness toward domain shift, and rapid prediction times. Its output works seamlessly with a previously published open-source pipeline for automatic ELS segmentation. IE-Vnet could serve as a core tool for high-volume trans-institutional studies of the inner ear. Code and pre-trained models are available free and open-source under https://github.com/pydsgz/IEVNet

Imperfections

This open access book synthesizes the swiftly growing critical scholarship on mistakes, glitches, and other aesthetics and logics of imperfection into the first transdisciplinary, transnational framework of imperfection studies. In recent years, the trend to present the notion of imperfection as a plus rather than a problem has resonated across a range of social and creative disciplines and a wealth of world localities. As digital tools allow media users to share ever more suave selfies and success stories, psychologists promote 'the gifts of imperfections' and point to perfectionism as a catalyst for rising depression and burnout complaints and suicide rates among millennials. As sound technologies increasingly permit musicians to 'smoothen' their work, composers increasingly praise glitches, noise, and cracks. As genetic engineering upgrades with swift speed, philosophers, marketeers, and physicians plea 'against perfection' and supermarkets successfully advertise 'perfectly imperfect' vegetables. Meanwhile, cultural analysts point at skewed perspectives, blurry images, and other 'deliberate imperfections' in new and historical cinema, painting, photography, music, and literature. While these and other experts applaud imperfection, scholars in fields ranging from disability studies to tourism critically interrogate a trend to fetishize imperfection and poverty. They rightfully warn against projecting privileged (and, often, emphatically western-biased) feel-good stories onto the less privileged, the distorted, and the frail. The editors unite the different strands in imperfection thinking across various disciplines tools. In fourteen chapters by experts from different world localities, they offer scholars and students more historically grounded and more critically informed conceptualizations of the imperfect. This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com

Imperfections:Studies in Mistakes, Flaws, and Failures

In recent years, the trend to present the notion of imperfection in a positive rather than negative light has resonated across a range of social and creative disciplines and a wealth of world regions. This open access book synthesizes the swiftly growing critical scholarship on mistakes, glitches, and other aesthetics and logics of imperfection into the first transdisciplinary, transnational framework of imperfection studies. With this framework, the editors offer scholars and students across various disciplines tools to craft more historically grounded and critically informed conceptualizations of the imperfect

Imperfections

This open access book synthesizes the swiftly growing critical scholarship on mistakes, glitches, and other aesthetics and logics of imperfection into the first transdisciplinary, transnational framework of imperfection studies. In recent years, the trend to present the notion of imperfection as a plus rather than a problem has resonated across a range of social and creative disciplines and a wealth of world localities. As digital tools allow media users to share ever more suave selfies and success stories, psychologists promote 'the gifts of imperfections' and point to perfectionism as a catalyst for rising depression and burnout complaints and suicide rates among millennials. As sound technologies increasingly permit musicians to 'smoothen' their work, composers increasingly praise glitches, noise, and cracks. As genetic engineering upgrades with swift speed, philosophers, marketeers, and physicians plea 'against perfection' and supermarkets successfully advertise 'perfectly imperfect' vegetables. Meanwhile, cultural analysts point at skewed perspectives, blurry images, and other 'deliberate imperfections' in new and historical cinema, painting, photography, music, and literature. While these and other experts applaud imperfection, scholars in fields ranging from disability studies to tourism critically interrogate a trend to fetishize imperfection and poverty. They rightfully warn against projecting privileged (and, often, emphatically western-biased) feel-good stories onto the less privileged, the distorted, and the frail. The editors unite the different strands in imperfection thinking across various disciplines tools. In fourteen chapters by experts from different world localities, they offer scholars and students more historically grounded and more critically informed conceptualizations of the imperfect. This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com

Independent Theatre in Contemporary Europe: Structures - Aesthetics - Cultural Policy

Over the past 20 years European theatre underwent fundamental changes in terms of aesthetic focus, institutional structure and in its position in society. The impetus for these changes was provided by a new generation in the independent theatre scene. This book brings together studies on the state of independent theatre in different European countries, focusing on the fields of dance and performance, children and youth theatre, theatre and migration and post-migrant theatre. Additionally, it includes essays on experimental musical theatre and different cultural policies for independent theatre scenes in a range of European countries