Table Of ContentAdvances 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
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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
