Information Technology in Biomedicine PDF
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Advances in Intelligent Systems and Computing 1011 Ewa Pietka Pawel Badura Jacek Kawa Wojciech Wieclawek Editors Information Technology in Biomedicine Advances in Intelligent Systems and Computing Volume 1011 Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Nikhil R. Pal, Indian Statistical Institute, Kolkata, India Rafael Bello Perez, Faculty of Mathematics, Physics and Computing, Universidad Central de Las Villas, Santa Clara, Cuba Emilio S. Corchado, University of Salamanca, Salamanca, Spain Hani Hagras, School of Computer Science & Electronic Engineering, University of Essex, Colchester, UK László T. Kóczy, Department of Automation, Széchenyi István University, Gyor, Hungary Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA Chin-Teng Lin, Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan Jie Lu, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia Patricia Melin, Graduate Program of Computer Science, Tijuana Institute of Technology, Tijuana, Mexico Nadia Nedjah, Department of Electronics Engineering, University of Rio de Janeiro, Rio de Janeiro, Brazil Ngoc Thanh Nguyen, Faculty of Computer Science and Management, Wrocław University of Technology, Wrocław, Poland Jun Wang, Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong Theseries“AdvancesinIntelligentSystemsandComputing”containspublications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing.Virtuallyalldisciplinessuchasengineering,naturalsciences,computer and information science, ICT, economics, business, e-commerce, environment, healthcare,lifesciencearecovered.Thelistoftopicsspansalltheareasofmodern intelligentsystemsandcomputingsuchas:computationalintelligence,softcomput- ingincludingneuralnetworks,fuzzysystems,evolutionarycomputingandthefusion of these paradigms, social intelligence, ambient intelligence, computational neuro- science, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming, knowledge-based paradigms, learning para- digms,machineethics,intelligentdataanalysis,knowledgemanagement,intelligent agents, intelligent decision making and support, intelligent network security, trust management,interactiveentertainment,Webintelligenceandmultimedia. The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings of important conferences, symposia and congresses. They cover significant recent developments in the field, both of a foundational and applicable character. An important characteristic feature of the series is the short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results. ** Indexing: The books of this series are submitted to ISI Proceedings, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink ** More information about this series at http://www.springer.com/series/11156 Ewa Pietka Pawel Badura (cid:129) (cid:129) Jacek Kawa Wojciech Wieclawek (cid:129) Editors Information Technology in Biomedicine 123 Editors EwaPietka Pawel Badura Faculty of Biomedical Engineering Faculty of Biomedical Engineering Silesian University of Technology Silesian University of Technology Zabrze,Poland Zabrze,Poland JacekKawa Wojciech Wieclawek Faculty of Biomedical Engineering Faculty of Biomedical Engineering Silesian University of Technology Silesian University of Technology Zabrze,Poland Zabrze,Poland ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems andComputing ISBN978-3-030-23761-5 ISBN978-3-030-23762-2 (eBook) https://doi.org/10.1007/978-3-030-23762-2 ©SpringerNatureSwitzerlandAG2019 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained hereinorforanyerrorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregard tojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface Information technology is a rapidly evolving discipline in medical data science, presenting one of the most significant potential for the future of health care. Multimodal acquisition systems, mobile devices, sensors, and AI-powered appli- cations give a new meaning to the optimization of clinical processes. Traditional signalandimagedataiscompletedbypatient-relatedandcase-relateddatawhichis able to reflect the patient condition and support the diagnosis, treatment, and physiotherapy procedures. The book includes nine parts that discuss various problemsrelatedtoproblem-dependantissuesaswellasgeneralapproachestodata acquisition, analysis, classification, and visualization.A special attentionis paid to Active and Assisted Living in aging society. More specifically, the thematic scope of particular parts includes the aspects listed below. Quantitative Data Analysis in Medical Diagnosis part addresses methods for processing of big quantitative medical data. Particular chapters discuss the biomedical image registration, visualization and modeling, data analysis, recogni- tion, and retrieval employed in detection and diagnosis support systems. Medical Data Science part presents original studies reporting on scientific approaches, especially pattern-recognition and machine-learning-based algorithms for interpretation of health-related, sensory data and ICT solutions toward pro- motingactiveandhealthylifestyleconnectedwithdemographicchangesleadingto society aging. DataMiningToolsandMethodsinMedicalApplicationspartcoversabroad range of medical data mining approaches in diagnostic applications and decision support systems including classical and convolutional neural networks and other artificial intelligence tools at the stage of feature selection and transformation, outlier detection, pattern recognition, and classification. Image Analysis part introduces multimodal data acquisition as well as 3D and 4D medical image analysis. Analytics in Action on SAS Platform part presents techniques including cognitive computing, deep learning, natural language processing, and machine learning combined with scalable, high-performance SAS platform in healthcare applications that may improve patient care. v vi Preface Biocybernetics in Physiotherapy part introduces biocybernetic support in innovative physiotherapy procedures by incorporating anthropometrics, data acquisition, and processing systems. Signal Processing and Analysis part indicates various approaches to the ECG signal analysis, noise estimation, and heart rate variability analysis. BiomechanicsandBiomaterialspartpresentstheevaluationofgaitstrategyon a treadmill based on frequency analysis, an assessment of the virtual reality influence on gait parameters, evaluation of muscle activities, and a study on biodegradable polymers technology. Medical Tools and Interfaces part presents studies on workstation interface design and medical informatics tools employed in diagnosis, treatment, and visualization. The editors would like to express their gratitude to all authors who contributed their original research reports as well as to all reviewers for their valuable com- ments.Yourefforthascontributedtothehighqualityofthebookthatwepassonto the readers. Zabrze, Poland Ewa Pietka June 2019 Contents Quantitative Data Analysis in Medical Diagnosis Functional Thermal Imaging of Skin Tissue Using the Discrete Thermal Time Constants Spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Maria Strąkowska, Robert Strąkowski, and Michał Strzelecki Contextual Classification of Tumor Growth Patterns in Digital Histology Slides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Zaneta Swiderska-Chadaj, Zhaoxuan Ma, Nathan Ing, Tomasz Markiewicz, Malgorzata Lorent, Szczepan Cierniak, Ann E. Walts, Beatrice S. Knudsen, and Arkadiusz Gertych Cervical Histopathology Image Classification Using Ensembled Transfer Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Chen Li, Dan Xue, Fanjie Kong, Zhijie Hu, Hao Chen, Yudong Yao, Hongzan Sun, Le Zhang, Jinpeng Zhang, Tao Jiang, Jianying Yuan, and Ning Xu Functional Kidney Analysis Based on Textured DCE-MRI Images . . . . 38 Marcin Kociołek, Michał Strzelecki, and Artur Klepaczko Incorporating Patient Photographs in the Radiology Image Acquisition and Interpretation Process. . . . . . . . . . . . . . . . . . . . . . . . . . 50 Elizabeth A. Krupinski Iterative Statistical Reconstruction Algorithm Based on C-C Data Model with the Direct Use of Projections Performed in Spiral Cone-Beam CT Scanners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Robert Cierniak and Piotr Pluta Deformable Mesh for Regularization of Three-Dimensional Image Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Piotr M. Szczypiński and Artur Klepaczko vii viii Contents Simulator for Modelling Confocal Microscope Distortions. . . . . . . . . . . 79 Katarzyna Sprawka and Piotr M. Szczypiński Medical Data Science Electromyography Based Translator of the Polish Sign Language. . . . . 93 Noemi Kowalewska, Przemysław Łagodziński, and Marcin Grzegorzek Electrooculography Application in Vision Therapy Using Smart Glasses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Maja Trzepacz, Przemysław Łagodziński, and Marcin Grzegorzek Assessment of Muscle Fatigue, Strength and Muscle Activation During Exercises with the Usage of Robot Luna EMG, Among Patients with Multiple Sclerosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Krystyna Stańczyk, Anna Poświata, Anna Roksela, and Michał Mikulski Information Models of Dynamics in Healthcare. . . . . . . . . . . . . . . . . . . 129 Václav Řepa Effects of External Conditions to Chaotic Properties of Human Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Radek Halfar, Martina Litschmannová, and Martin Černý A Preliminary Evaluation of Transferring the Approach Avoidance Task into Virtual Reality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Tanja Joan Eiler, Armin Grünewald, Alla Machulska, Tim Klucken, Katharina Jahn, Björn Niehaves, Carl Friedrich Gethmann, and Rainer Brück Data Mining Tools and Methods in Medical Applications Convolutional Neural Networks in Speech Emotion Recognition – Time-Domain and Spectrogram-Based Approach . . . . . . 167 Bartłomiej Stasiak, Sławomir Opałka, Dominik Szajerman, and Adam Wojciechowski Convolutional Neural Networks for Computer Aided Diagnosis of Interdental and Rustling Sigmatism. . . . . . . . . . . . . . . . . . . . . . . . . . 179 Andre Woloshuk, Michal Krecichwost, Zuzanna Miodonska, Dominika Korona, and Pawel Badura Barley Defects Identification by Convolutional Neural Networks. . . . . . 187 Michał Kozłowski and Piotr M. Szczypiński Wavelet Convolution Neural Network for Classification of Spiculated Findings in Mammograms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Magdalena Jasionowska and Aleksandra Gacek Contents ix Weakly Supervised Cervical Histopathological Image Classification Using Multilayer Hidden Conditional Random Fields . . . . . . . . . . . . . . 209 ChenLi,HaoChen,DanXue,ZhijieHu,LeZhang,LiangziHe,NingXu, Shouliang Qi, He Ma, and Hongzan Sun A Survey for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 Chen Li, Dan Xue, Zhijie Hu, Hao Chen, Yudong Yao, Yong Zhang, Mo Li, Qian Wang, and Ning Xu Image Analysis Descriptive Seons: Measure of Brain Tissue Impairment. . . . . . . . . . . . 237 Artur Przelaskowski, Ewa Sobieszczuk, and Izabela Domitrz An Automatic Method of Chronic Wounds Segmentation in Multimodal Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Joanna Czajkowska, Marta Biesok, Jan Juszczyk, Agata Wijata, Bartłomiej Pyciński, Michal Krecichwost, and Ewa Pietka Evaluation of Methods for Volume Estimation of Chronic Wounds. . . . 258 Jan Juszczyk, Agata Wijata, Joanna Czajkowska, Marta Biesok, Bartłomiej Pyciński, and Ewa Pietka Infrared and Visible Image Fusion Objective Evaluation Method . . . . . 268 Daniel Ledwoń, Jan Juszczyk, and Ewa Pietka Wavelet Imaging Features for Classification of First-Episode Schizophrenia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 Kateřina Maršálová and Daniel Schwarz Dynamic Occlusion Surface Estimation from 4D Multimodal Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292 Agnieszka A. Tomaka, Leszek Luchowski, Dariusz Pojda, and Michał Tarnawski Evaluation of Dental Implant Stability Using Radiovisiographic Characterization and Texture Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 304 Marta Borowska and Janusz Szarmach Patella – Atlas Based Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 Piotr Zarychta Analytics in Action on SAS Platform De-Identification of Electronic Health Records Data . . . . . . . . . . . . . . . 325 Piotr Borowik, Piotr Brylicki, Mariusz Dzieciątko, Waldemar Jęda, Łukasz Leszewski, and Piotr Zając
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