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arXiv 2025年

作者： Gierke, Julia Peter, Pascal Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University Campus E1.7 Saarbrücken66041 Germany

The medial axis transform is a well-known tool for shape recognition. Instead of the object contour, it equivalently describes a binary object in terms of a skeleton containing all centres of maximal inscribed discs. While this shape descriptor is useful for many applications, it is also sensitive to noise: Small boundary perturbations can result in large unwanted expansions of the skeleton. Pruning offers a remedy by removing unwanted skeleton parts. In our contribution, we generalise this principle to skeleton sparsification: We show that subsequently removing parts of the skeleton simplifies the associated shape in a hierarchical manner that obeys scale-space properties. To this end, we provide both a continuous and discrete theory that incorporates architectural and simplification statements as well as invariances. We illustrate how our skeletonisation scale-spaces can be employed for practical applications with two proof-of-concept implementations for pruning and compression. Copyright © 2025, The Authors. All rights reserved.

关键词： Musculoskeletal system

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Covid severity prediction: Who cares about the data quality?

Covid severity prediction: Who cares about the data quality?

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2022 International Conference on Frontiers of Information Technology, FIT 2022

作者： Nae, Teodora Krabbe, Johannes Bukhsh, Faiza Allah Jayasinghe Arachchige, Jeewanie Ahmed, Faizan University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands Medische Spectrum Twente Enschede Netherlands University of Ruhuna Department of Computer Science Matara Sri Lanka University of Twente Formal Methods and Tools Group Enschede Netherlands

ISBN: (纸本)9798350345933

COVID-19 is an ongoing pandemic disrupting daily life and overwhelming the healthcare infrastructure. Since the outburst of the pandemic, researchers have used various techniques to predict many aspects of the disease, including mortality rate and severity. The reproducibility of this research is challenging due to varying methodologies used to collect data, data quality, vague description of methodological approach to training prediction models, over-relying on data imputation, and over-fitting. This paper focuses on these challenges and provides a short yet comprehensive review of research on COVID mortality and severity prediction. The emphasis is on the reproducibility of the results and data quality issues. To further elaborate on the issue, we report the development of severity prediction models using two data sets. CRISP-DM is used as a methodological approach. We analyze and criticize the quality of the used data sets and how they affect the performance and limitations of the trained models. We conclude this paper with comments on data quality issues, the importance of reproducibility, and suggestions to improve reproducibility. © 2022 IEEE.

关键词： COVID-19

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Efficient Representations of the Diffusion Echo

Efficient Representations of the Diffusion Echo

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10th International Conference on Scale Space and Variational Methods in computer Vision, SSVM 2025

作者： Gaa, Daniel Weickert, Joachim Farag, Iva Çiçek, Özgün Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University Campus E1.7 Saarbrücken66041 Germany

ISBN: (纸本)9783031923685

Diffusion echoes are a fundamental concept for understanding the behaviour of nonlinear diffusion filters. They describe the accumulated data exchange during a diffusion process and are given by the columns or rows of the corresponding state transition matrix. Unfortunately, they involve a prohibitively large amount of data. Therefore, we propose the first compression strategy to efficiently represent and reconstruct diffusion echoes. Using a truncated singular value decomposition (SVD) we can reduce the storage requirements substantially, while still obtaining very accurate reconstructions. The SVD works on all echoes jointly and captures the redundancy between them. To approximate the singular value decomposition, we use a powerful probabilistic approach: the randomised subspace iteration. We show on a test case with a difficult, rapidly decaying diffusivity that we can reduce the storage requirements by a factor of 20, without creating visually noticeable errors. Furthermore, our compressed data representation enables an efficient reconstruction, which allows a fast and detailed echo investigation. This paves the way for various future applications of the diffusion echo that have been prevented by its huge amount of data so far. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Compression Diffusion Echoes Impulse Response Singular Value Decomposition

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Automatic Objective Severity Grading of Peripheral Facial Palsy Using 3D Radial Curves Extracted from Point Clouds 32

Automatic Objective Severity Grading of Peripheral Facial Pa...

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32nd Medical Informatics Europe Conference, MIE 2022

作者： Büchner, Tim Sickert, Sven Volk, Gerd Fabian Guntinas-Lichius, Orlando Denzler, Joachim Friedrich Schiller University Jena Faculty of Mathematics and Computer Science Computer Vision Group Ernst-Abbe-Platz 2 Jena7743 Germany Jena University Hospital Department of Otorhinolaryngology Friedrich Schiller University Jena Germany

ISBN: (纸本)9781643682846

Peripheral facial palsy is an illness in which a one-sided ipsilateral paralysis of the facial muscles occurs due to nerve damage. Medical experts utilize visual severity grading methods to estimate this damage. Our algorithm-based method provides an objective grading using 3D point clouds. We extract from static 3D recordings facial radial curves to measure volumetric differences between both sides of the face. We analyze five patients with chronic complete peripheral facial palsy to evaluate our method by comparing changes over several recording sessions. We show that our proposed method allows an objective assessment official palsy. © 2022 European Federation for Medical Informatics (EFMI) and IOS Press.

关键词： Grading

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Automated Pattern-Based Recommendation for Improving API Operation Performance and Reliability in Cloud-Based architectures

Automated Pattern-Based Recommendation for Improving API Ope...

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Software Services Engineering (SSE) IEEE International Conference on

作者： Amine El Malki Uwe Zdun UniVie Doctoral School Computer Science DoCS University of Vienna Vienna Austria Research Group Software Architecture Faculty of Computer Science University of Vienna Vienna Austria

The extensive use of APIs as the entry point to many Cloud-based applications has created challenging problems, especially concerning API quality properties such as performance and reliability. API best practices and patterns, such as bundling requests, rate limiting, or load balancing, have been proposed to solve these challenges. Unfortunately, no study investigating the impact of existing API practices and patterns on such quality properties exists beyond informal recommendations. In this paper, we fill this gap by proposing a pattern-based, automated recommendation approach to improve the performance and reliability of API operations. We provide a benchmark suite based on a realistic open-source microservice application to enable the automatic generation of comprehensive decision tree models. These models are then processed to generate API design recommendation algorithms to improve API operations regarding performance and reliability stored in catalogs for reuse. We validate our algorithms using extensive data sets generated by running the benchmark on a private cloud and AWS. For both environments, based on the decision tree models automatically generated from the measured data, API design recommendation algorithms have been calculated using our approach.

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Identification of Diagnostic Biomarkers for Cardiovascular Diseases and Diabetes Mellitus Through Raman Spectroscopy and Machine Learning Algorithms 16

Identification of Diagnostic Biomarkers for Cardiovascular D...

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16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Wilson, Megan Obe, Dhiya Al-Jumeily Abbas, Ismail Khan, Iftikhar Birkett, Jason Tang, Leung Assi, Sulaf Liverpool John Moores University Pharmacy and Biomolecular Sciences Liverpool United Kingdom Liverpool John Moores University Computer Science and Mathematics Liverpool United Kingdom Lebanese University Faculty of Science Beirut Lebanon Chemical Analysis Group Agilent Technology United Kingdom

ISBN: (纸本)9798350381344

The use of handheld Raman spectroscopy has increased in popularity based on its ability to provide portable and rapid analysis of endogenous compounds and diagnostic biomarkers in alternative biological matrices, such as fingernails. The application of fingernails as a diagnostic matrix allows for non-invasive, non-intrusive sampling, which can be carried out in the comfort of the patient's home. This study aimed to identify diagnostic biomarkers in fingernails related to cardiovascular diseases (CVDs) and diabetes mellitus (DM) using Raman spectroscopy and machine learning algorithms (MLAs). The findings showed that Raman spectroscopy successfully identified the presence of disease specific biomarkers in CVD and diabetic fingernails. Furthermore, when used in combination with MLAs, Raman spectroscopy was able to differentiate between healthy, CVD and diabetic fingernails. Further investigation will look at applying additional MLAs for determining the prognosis of disease. © 2023 IEEE.

关键词： Machine learning

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Respiratory Motion Compensation and Haptic Feedback for X-Ray-Guided Teleoperated Robotic Needle Insertion

Respiratory Motion Compensation and Haptic Feedback for X-Ra...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ana Cordón Avila Mostafa Selim Momen Abayazid Faculty of Electrical Engineering Robotics and Mechatronics research group TechMed Centre Mathematics and Computer Science University of Twente AE Enschede The Netherlands

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Respiratory motion limits the accuracy and pre-cision of abdominal percutaneous procedures. In this paper, respiratory motion is compensated robotically using motion estimation models. Additionally, a teleoperated insertion is performed using proximity-based haptic feedback to guide physicians during insertion, enabling a radiation-free remote insertion for the end-user. The study has been validated using a robotic liver phantom, and five insertions were performed. The resulting motion estimation errors were below 3 mm for all directions of motion, and the overall resulting 3D insertion errors were 2.60 mm, 7.75 mm, and 2.86 mm for the superior-inferior, lateral, and anterior-posterior directions of motion, respectively. The proposed approach is expected to minimize the chances of inaccurate treatment or diagnosis due to respiratory-induced motion and reduce radiation exposure. A video summary can be found in: https://***/2Xw6AMe2mco

关键词： Three-dimensional displays Motion estimation Liver Phantoms Medical services Biomechatronics Needles Motion compensation Haptic interfaces Robots

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Palm-sized Near-Infrared Spectroscopy and Machine Learning Analytics for the Detection of Endogenous Constituents and Drugs in Human Fingernails 15

Palm-sized Near-Infrared Spectroscopy and Machine Learning A...

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15th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Wilson, Megan Obe, Dhiya Al-Jumeily Abbas, Ismail Khan, Iftikhar Birkett, Jason Tang, Leung Assi, Sulaf Pharmacy and Biomolecular Sciences Liverpool John Moores University Liverpool United Kingdom Liverpool John Moores University Computer Science and Mathematics Liverpool United Kingdom Lebanese University Faculty of Science Beirut Lebanon Chemical Analysis Group Agilent Technology United Kingdom

ISBN: (纸本)9798350335149

Near infrared (NIR) spectroscopy offers portable and rapid analysis of endogenous constituents and drugs within fingernails. Fingernails are a useful alternative biological matrix to blood and urine specimen as they provide the advantage of being non-invasive and require minimal sample size (1-3 mm). This work utilised NIR spectroscopy for the detection of (1) drugs in fingernails including benzocaine, calcium carbonate, cocaine hydrochloride (HCl), levamisole HCl, lidocaine HCl and procaine HCl;and (2) endogenous constituents such as carbohydrates, lipids, proteins and water. Fingernails were analysed initially 'as received' to identify the aforementioned endogenous constituents. Seven sets of fingernails were then spiked with one the identified drugs and measured over a six-week period. Spectra were exported into Matlab 2019a for spectral interpretation and machine learning analytics (MLAs). MLAs included correlation wavenumber space (CWS), principal component analysis (PCA) and Artificial Neural Networks Self-Organising Maps (SOM). The results showed that NIR spectra of spiked nails showed key characteristic features at specific wavelengths that corresponded to their spiked drug (1). When combined with CWS and PCA, NIR spectroscopy was able to differentiate between spiked and un-spiked nails and distinguish between the drugs that did not share similar chemical structures. CWS values (r values) and PCA loading scores highlighted spectra/spectral features that were significant. In addition, SOM showed further classes beyond PCA that corresponded to changes in physical properties of the fingernails. Thus, finding confirmed that NIR spectroscopy combined with MLAs possessed the ability to characterise fingernails based on their endogenous constituents and to detect the presence of drugs within fingernails. © 2023 IEEE.

关键词： Principal component analysis

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Segment Intersection Representations, Level Planarity and Constrained Ordering Problems

arXiv

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arXiv 2025年

作者： Fink, Simon D. Pfretzschner, Matthias Stumpf, Peter Algorithms and Complexity Group Technische Universität Wien Austria Faculty of Computer Science and Mathematics University of Passau Germany Department of Theoretical Computer Science Faculty of Information Technology Czech Technical University Prague Czech Republic Department of Applied Mathematics Charles University Prague Czech Republic

In the Segment Intersection Graph Representation Problem, we want to represent the vertices of a graph as straight line segments in the plane such that two segments cross if and only if there is an edge between the corresponding vertices. This problem is NP-hard (even ∃R-complete [19]) in the general case [13] and remains so if we restrict the segments to be axis-aligned, i.e., horizontal and vertical [12]. A long standing open question for the latter variant is its complexity when the order of segments along one axis (say the vertical order of horizontal segments) is already given [12,14]. We resolve this question by giving efficient solutions using two very different approaches that are interesting on their own. First, using a graph-drawing perspective, we relate the problem to a variant of the well-known Level Planarity problem, where vertices have to lie on preassigned horizontal levels. In our case, each level also carries consecutivity constraints on its vertices;this Level Planarity variant is known to have a quadratic solution. Second, we use an entirely combinatorial approach and show that both problems can equivalently be formulated as a linear ordering problem subject to certain consecutivity constraints. While the complexity of such problems varies greatly, we show that in this case the constraints are well-structured in a way that allows a direct quadratic solution. Thus, we obtain three different-but-equivalent perspectives on this problem: the initial geometric one, one from planar graph drawing and a purely combinatorial one. © 2025, CC BY.

关键词： Graph theory

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Mathematical Modelling of Nonlinear Heat Conduction with Relaxing Boundary Conditions 1

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10th International Conference on Numerical Methods and Applications, NMA 2022

作者： Filipov, Stefan M. Faragó, István Avdzhieva, Ana Department of Computer Science Faculty of Chemical and System Engineering University of Chemical Technology and Metallurgy Sofia Bulgaria Department of Differential Equations Institute of Mathematics Budapest University of Technology and Economics & MTA-ELTE Research Group Budapest Hungary Faculty of Mathematics and Informatics "St. Kl. Ohridski" University of Sofia Sofia Bulgaria

ISBN: (数字)9783031324123

ISBN: (纸本)9783031324116

This paper considers one dimensional unsteady heat condition in a media with temperature dependent thermal conductivity. When the thermal conductivity depends on the temperature, the corresponding heat equation is nonlinear. At one or both boundaries, a relaxing boundary condition is applied. It is a time dependent condition that approaches continuously, as time increases, a certain time independent condition. Such behavior at the boundaries arises naturally in some physical systems. As an example, we propose a simple model system that can give rise to either Dirichlet or convective relaxing boundary condition. Due to the dependence of the thermal conductivity on the temperature, the convective condition is nonlinear. For the solution of the problem, we propose a new numerical approach that first discretizes the heat equation in time, whereby a sequence of two-point boundary value problems (TPBVPs) is obtained. We use implicit time discretization, which provides for unconditional stability of the method. If the initial condition is given, we can solve consecutively the TPBVPs and get approximations of the temperature at the different time levels. For the solution of the TPBVPs, we apply the finite difference method. The arising nonlinear systems are solved by Newton’s method. A number of example problems are solved demonstrating the efficiency of the proposed approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Boundary conditions

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