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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

Correction to: Biomarkers and neuromodulation techniques in substance use disorders

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Bioelectronic medicine 2020年第1期6卷 6页

作者： Bettina Habelt Mahnaz Arvaneh Nadine Bernhardt Ivan Minev 1Department of Psychiatry and Psychotherapy Medical Faculty Carl Gustav Carus Technische Universität Dresden Dresden Germany. 2Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK.

[This corrects the article DOI: 10.1186/s42234-020-0040-0.].

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High-bandwidth tribometry as a means of recording natural textures 7

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High-bandwidth tribometry as a means of recording natural te...

7th IEEE World Haptics Conference, WHC 2017

作者： Grigorii, Roman V. Peshkin, Michael A. Colgate, J. Edward Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (纸本)9781509014255

The measurement of perceptually relevant information about textures has been approached through profilometry, vibrometry, and tribometry. Manfredi et al. [1] used a laser Doppler vibrometer to measure skin surface vibrations as a texture sample slides across a fingertip. In our work, we treat the Manfredi et al. measurements as a gold standard, and assess the performance of a simpler and more portable device: A high-bandwidth tribometer. The tribometer was used to measure shear and normal forces applied to each of six texture samples as a fingertip scanned across them. The collected data was used to build two classifiers: One based on features extracted from the spectra (which treats the data as stationary);and a second based on the first through fourth order statistics associated with a set of band-pass filters (which treats the data as nonstationary). The results indicate that tribometry, while not as effective as vibrometry, may nonetheless prove effective as a means of recording natural texture. Additionally, we find that the non-stationarity of skin vibrations may serve as means of texture classification. Ongoing work aims to couple tribometric recordings with texture rendering and playback via surface haptic devices, and to understand the perceptual significance of non-stationarity in vibrations. © 2017 IEEE.

关键词： Bandpass filters

Gaussian Processes for RSS Fingerprints Construction in Indoor Localization

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Gaussian Processes for RSS Fingerprints Construction in Indo...

International Conference on Information Fusion

作者： Yuxin Zhao Chao Liu Lyudmila S. Mihaylova Fredrik Gunnarsson Ericsson Research Linköping Sweden Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Location-based applications attract more and more attention in recent years. Examples of such applications include commercial advertisements, social networking software and patient monitoring. The received signal strength (RSS) based location fingerprinting is one of the most popular solutions for indoor localization. However, there is a big challenge in collecting and maintaining a relatively large RSS fingerprint database. In this work, we propose and compare two algorithms namely, the Gaussian process (GP) and Gaussian process with variogram, to estimate and construct the RSS fingerprints with incomplete data. The fingerprint of unknown reference points is estimated based on measurements at a limited number of surrounding locations. To validate the effectiveness of both algorithms, experiments using Bluetooth-low-energy (BLE) infrastructure have been conducted. The constructed RSS fingerprints are compared to the true measurements, and the result is analyzed. Finally, using the constructed fingerprints, the localization performance of a probabilistic fingerprinting method is evaluated.

关键词： Indoor localization Received signal strength Gaussian process Variogram Location fingerprinting

Infinitesimal weak rigidity, formation control of three agents, and extension to 3-dimensional space

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arXiv 2018年

作者： Kwon, Seong-Ho Trinh, Minh Hoang Oh, Koog-Hwan Zhao, Shiyu Ahn, Hyo-Sung Gwangju Korea Republic of Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

In this paper, we introduce new concepts of weak rigidity matrix and infinitesimal weak rigidity for planar frameworks. The weak rigidity matrix is used to directly check if a framework is infinitesimally weakly rigid while previous work can check a weak rigidity of a framework indirectly. An infinitesimal weak rigidity framework can be uniquely determined up to a translation and a rotation (and a scaling also when the framework does not include any edge) by its inter-neighbor distances and angles. We apply the new concepts to a three-agent formation control problem with a gradient control law, and prove instability of the control system at any incorrect equilibrium point and convergence to a desired target formation. Also, we propose a modified Henneberg construction, which is a technique to generate minimally rigid (or weakly rigid) graphs. Finally, we extend the concept of the weak rigidity in R2 to the concept in R3. Copyright © 2018, The Authors. All rights reserved.

关键词： Rigidity

Spatio-temporal structured sparse regression with hierarchical gaussian process priors

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arXiv 2018年

作者： Kuzin, Danil Isupova, Olga Mihaylova, Lyudmila Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom

—This paper introduces a new sparse spatio-temporal structured Gaussian process regression framework for online and offline Bayesian inference. This is the first framework that gives a time-evolving representation of the interdependencies between the components of the sparse signal of interest. A hierarchical Gaussian process describes such structure and the interdependencies are represented via the covariance matrices of the prior distributions. The inference is based on the expectation propagation method and the theoretical derivation of the posterior distribution is provided in the paper. The inference framework is thoroughly evaluated over synthetic, real video and electroencephalography (EEG) data where the spatio-temporal evolving patterns need to be reconstructed with high accuracy. It is shown that it achieves 15% improvement of the F-measure compared with the alternating direction method of multipliers, spatio-temporal sparse Bayesian learning method and one-level Gaussian process model. Additionally, the required memory for the proposed algorithm is less than in the one-level Gaussian process model. This structured sparse regression framework is of broad applicability to source localisation and object detection problems with sparse signals. Copyright © 2018, The Authors. All rights reserved.

关键词： Electrophysiology

Spicule jets in the solar atmosphere modeled with resistive MHD and thermal conduction

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arXiv 2020年

作者： González-Avilés, J.J. Guzmán, F.S. Fedun, V. Verth, G. CONACyT - Servicio de Clima Espacial México - Laboratorio Nacional de Clima Espacial SCiESMEX-LANCE. MoreliaMichoacán Mexico Instituto de Geofísica Unidad Michoacán Universidad Nacional Autónoma de México MoreliaMichoacán Mexico Laboratorio de Inteligencia Artificial y Supercómputo Instituto de Física y Matemáticas Universidad Michoacana de San Nicolás de Hidalgo. MoreliaMichoacán Mexico Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom School of Mathematics and Statistics University of Sheffield SheffieldS3 7RH United Kingdom

Using numerical simulations, we study the effects of magnetic resistivity and thermal conductivity in the dynamics and properties of solar jets with characteristics of Type II spicules and cool coronal jets. The dynamic evolution of the jets is governed by the resistive MHD equations with thermal conduction along the magnetic field lines on a 2.5D slice. The magnetic field configuration consists of two symmetric neighboring loops with opposite polarity, used to support reconnection and followed by the plasma jet formation. In total 10 simulations were carried out with different values of resistivity and thermal conductivity, that produce jets with different morphological and thermal properties we quantify. We find that an increase in magnetic resistivity does not produce significant effects on the morphology, velocity and temperature of the jets. However, thermal conductivity affects both temperature and morphology of the jets. In particular, thermal conductivity causes jets to reach greater heights and increases the temperature of the jet-apex. Also, heat flux maps indicate the jet-apex and corona interchange energy more efficiently than the body of the jet. These results could potentially open a new avenue for plasma diagnostics in the Sun’s atmosphere. Copyright © 2020, The Authors. All rights reserved.

关键词： Morphology

Wind Turbine Blade Condition Monitoring and Damage Detection by Image-Based Method and Frequency-Based Analysis

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Wind Turbine Blade Condition Monitoring and Damage Detection...

International Conference on Modelling, Identification and control (ICMIC)

作者： Jiansheng Yang Ling Zhao Zi-Qiang Lang Yang Zhang Jiansheng Yang is with the Electrical Engineering College Guizhou University Guiyang China Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield Department of Mechanical Engineering The University of Sheffield Sheffield

Wind turbine blade condition monitoring is necessary for planning blade maintenance. In this paper, a wind turbine blade condition monitoring and damage detection based on vibration measurement using a image-based system is proposed. Blade are measured in undamaged and damaged conditions under various vibration frequencies and displacement amplitudes. The results were compared and analysed in both time and frequency domains. Then a frequency-based index is proposed to quantify the vibration dynamics and detect the damage.

关键词： Blades Vibrations Wind turbines Condition monitoring Frequency measurement Vibration measurement Harmonic analysis

Nonlinear dynamic predictive model selection and interference using information criteria 23

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Nonlinear dynamic predictive model selection and interferenc...

23rd IEEE International Conference on Automation and Computing, ICAC 2017

作者： Gu, Yuanlin Wei, Hua-Liang Balikhin, Michael A. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9780701702618

Model selection is a crucial step in choosing a best model from a series of candidate models for data based modelling problems. The commonly used Akaike information criterion (AIC) and Bayesian information criteria (BIC) may not be effective for many real-world modelling problems when the true system model structure is unknown and therefore not included in the candidate model set. This study investigates the model selection issue using AIC, BIC and an adjustable prediction error sum of squares (APRESS) for nonlinear dynamic predictive modelling. Results from simulation and real data modelling case studies show that both BIC and APRESS produce good models for nonlinear modelling problems. The APRESS works slightly better than BIC in achieving a parsimonious representation of the studied system. In addition, a model averaging method is introduced, which is capable to provide an averaged model that is more robust in generalization (i.e. in representing future data) than any single model. © 2017 Chinese Automation and Computing Society in the UK - CACSUK.

关键词： Automation