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Search results for: MEDICAL IMAGE ANALYSIS
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HEALTH MONITORING OF A COMPRESSION IGNITION ENGINE FED WITH DIFFERENT LOW-SULPHUR MARINE FUELS BY ENDOSCOPIC IMAGE PROCESSING AND ANALYSIS
PublicationThis article characterises the methodology for the endoscopic testing of a laboratory diesel engine used for testing marine fuels. The ‘Shadow’ measurement method used in the XLG3 type EVEREST digital endoscope, for quantitative and qualitative identification of detected surface defects, was approximated. Representative endoscopic images of the elements limiting the working space of the research engine are demonstrated, having...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Digital Photogrammetry in the Analysis of the Ventricles' Shape and Size
PublicationThis article presents spatial analyzes conducted to assess the potential of ReMake software to be used for medical purposes, with emphasis on the analysis of the shape and dimensions of the ventricles. To achieve this goal, the length of the sections measured with the ReMake and Image Master programs have been compared. RMS error was on the level of 1.2 mm. In addition to indicating the appropriateness of using this software, there...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Multimodal human-computer interfaces based on advanced video and audio analysis
PublicationMultimodal interfaces development history is reviewed briefly in the introduction. Examples of applications of multimodal interfaces to education software and for the disabled people are presented, including interactive electronic whiteboard based on video image analysis, application for controlling computers with mouth gestures and the audio interface for speech stretching for hearing impaired and stuttering people. The Smart...
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Using Eye-tracking to get information on the skills acquisition by the radiology residents
PublicationThis paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained...
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Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
PublicationAccurate segmentation of cellular nuclei is imperative for various biological and medical applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline employing microscopic examination of bodily tissues, serves as a cornerstone for cancer diagnosis. Nonetheless, the conventional histopathological diagnosis process is frequently marred by time constraints and potential inaccuracies. Consequently, there...
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Parallelization of video stream algorithms in kaskada platform
PublicationThe purpose of this work is to present different techniques of video stream algorithms parallelization provided by the Kaskada platform - a novel system working in a supercomputer environment designated for multimedia streams processing. Considered parallelization methods include frame-level concurrency, multithreading and pipeline processing. Execution performance was measured on four time-consuming image recognition algorithms,...
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Evaluation of Respiration Rate Using Thermal Imaging in Mobile Conditions
PublicationRespiratory rate is very important vital sign that should be measured and documented in many medical situations. The remote measurement of respiration rate can be especially valuable for medical screening purposes (e.g. severe acute respiratory syndrome (SARS), pandemic influenza, etc.). In this chapter we present a review of many different studies focused on the measurements and estimation of respiration rate using thermal imaging...
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A Mammography Data Management Application for Federated Learning
PublicationThis study aimed to develop and assess an application designed to enhance the management of a local client database consisting of mammographic images with a focus on ensuring that images are suitably and uniformly prepared for federated learning applications. The application supports a comprehensive approach, starting with a versatile image-loading function that supports DICOM files from various medical imaging devices and settings....
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublicationCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Art and Healthcare - Healing Potential of Artistic Interventions in Medical Settings
PublicationThe stereotype of a machine for healing seems to be well rooted in common thinking and social perception of hospital buildings. The technological aspect of healthcare architecture has been influenced for several years by three major factors. The first is linked to the necessity of providing safety and security in the environment of elevated epidemiological risk. The second concerns the need for incorporating advanced technology...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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The Use of Liquid Crystal Thermography in Selected Technical and Medical Applications—Recent Development
PublicationThermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLC at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make the temperature and velocity fields in liquids visible...
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Analogue CMOS ASICs in Image Processing Systems
PublicationIn this paper a survey of analog application specific integrated circuits (ASICs) for low-level image processing, called vision chips, is presented. Due to the specific requirements, the vision chips are designed using different architectures best suited to their functions. The main types of the vision chip architectures and their properties are presented and characterized on selected examples of prototype integrated circuits (ICs)...
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UPDRS tests for diagnosis of Parkinson's disease employing virtual-touchpad
PublicationThis paper presents a new approach to diagnosing Parkinson's disease. The progression of the disease can be measured by the UPDRS (Unified Parkinson Disease Rating Scale) scale which is used to evaluate motor and behavioral symptoms of Parkinson's disease. Hitherto the evaluation of the advancement of the disease in the UPDRS scale was made by a specialist through medical observation. The authors suggest a partial automation of...
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New Applications of Multimodal Human-Computer Interfaces
PublicationMultimodal computer interfaces and examples of their applications to education software and for the disabled people are presented. The proposed interfaces include the interactive electronic whiteboard based on video image analysis, application for controlling computers with gestures and the audio interface for speech stretching for hearing impaired and stuttering people. Application of the eye-gaze tracking system to awareness...
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Non invasive optical cellular imaging in humans.
PublicationOne of the most appealing and still unsolved problems in biological and medical imaging is the possibility of noninvasive visualization of tissue in vivo with an accuracy of microscopic examination. A major difficulty to solve in biomedical imaging is a degradation of image quality caused by the presence of optical inhomogeneity of tissue. Is there any chance to develop a microscopic method that allows non-invasive observation...
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Trustworthy Applications of ML Algorithms in Medicine - Discussion and Preliminary Results for a Problem of Small Vessels Disease Diagnosis.
PublicationML algorithms are very effective tools for medical data analyzing, especially at image recognition. Although they cannot be considered as a stand-alone diagnostic tool, because it is a black-box, it can certainly be a medical support that minimize negative effect of human-factors. In high-risk domains, not only the correct diagnosis is important, but also the reasoning behind it. Therefore, it is important to focus on trustworthiness...
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Assessment of particular abdominal aorta section extraction from contrast-enhanced computed tomography angiography
PublicationThe aim of this work is to improve the accuracy of extraction of a particular abdominal aorta section and to reduce the distortion in three-dimensional Computed Tomography Angiography (CTA) images. Imaging modality and quality plays crucial role in the medical diagnostic process, thus ensuring high quality of images is essential at every stage of acquisition and processing.Noise is defined as a disturbance of the image quality...
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Redefiniowanie przestrzeni medycznej = Redefining healthcare space
PublicationSzpital jest obiektem publicznym, budynkiem-miastem, jego architektura nakierowana jest na realizację procesu leczenia i zdrowienia, a jednocześnie formuje przestrzenne ramy mikrokosmosu interakcji społecznych rozgrywających się pomiędzy pacjentami i personelem, gośćmi i „mieszkańcami”. Współcześnie w podejściu do rozumienia czym jest szpital - a zatem również do kształtowania architektury obiektów medycznych - można zauważyć dwa...
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An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublicationThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
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POTENCJALNE MOŻLIWOŚCI APLIKACJ TECHNIKI E-NOS W DIAGNOSTYCE MEDYCZNEJ=APPLICATION POTENTIALITIES OF E-NOSE TECHNIQUE IN MEDICAL DIAGNOSTICS
PublicationW pracy przedstawiono i omówiono zasadę działania instrumentu analitycznego - elektronicznego nosa (e-nos) zdolnego rozróżnić i sklasyfikować intensywność zapachu. Urządzenia te służą do automatycznej analizy i rozróżniania próbek zapachowych o złożonym składzie, do rozpoznawania ich charakterystycznych właściwości i najczęściej przeznaczone są do szybkiej analizy jakościowej. Dzięki unikatowym właściwościom technika ta znalazła...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublicationDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Elektroniczne instrumenty komunikacji marketingowej w marketingu usług medycznych
PublicationNie ma wątpliwości, że wielu polskich świadczeniodawców usług zdrowotnych korzysta z Internetu do komunikowania się z pacjentami. Jednocześnie chcą oni stworzyć wizerunek marki jako bardziej nowoczesnej i atrakcyjnej. Elektroniczna komunikacja marketingowa (szczególnie serwisy informacyjne, serwisy społecznościowe, blogi, fora, microblogi, wyszukiwarki, marketing mobilny) ma coraz większe znaczenie w marketingu usług medycznych,...
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Template chart detection for stoma telediagnosis
PublicationThe paper presents the concept of using color template charts for the needs of telemedicine, particularly telediagnosis of the stoma. Although the concept is not new, the current popularity and level of development of digital cameras, especially those embedded in smartphones, allow common and reliable remote advice on various medical problems, which can be very important in the case of limitations in a physical contact with a doctor....
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Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
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Semantic segmentation training using imperfect annotations and loss masking
PublicationOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
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The Digital Tissue and Cell Atlas and the Virtual Microscope
PublicationWith the cooperation of the CI TASK (Center of lnformatics Tri-Citry Academic Supercomputer and network) and the Gdańsk University of Technology, the Medical University of Gdańsk undertook the creation of the Digital Tissue and Cell Atlas and the Virtual Microscope for the needs of the Bridge of Data project. In the beginning, an extensive collection of histological and cytological slides was carefully selected and prepared by...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Platforma KASKADA jako system zapewniania bezpieczeństwa poprzez masową analizę strumieni multimedialnych w czasie rzeczywistym
PublicationW artykule przedstawiono Platformę KASKADA rozumianą jako system przetwarzania danych cyfrowych i strumieni multimedialnych oraz stanowiącą ofertę usług wspomagających zapewnienie bezpieczeństwa publicznego, ocenę badań medycznych i ochronę własności intelektualnej. celem prowadzonych prac było stworzenie innowacyjnego systemu umozliwiajacego wydajną i masową analizę dokumentów cyfrowych i strumieni multimedialnych w czasie rzeczywistym...
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Modeling of Human Tissue for Medical Purposes
PublicationThe paper describes the possibilities offered for medicine by modeling of human tissue using virtual and augmented reality. It also presents three proposals of breast modeling for the use in clinical practice. These proposals are the result of arrangements of medical and computer scientists team (the authors) and will be pursued and implemented in the near future. There is included also a brief description of the most popular methods...
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Zdolności dynamiczne do budowania chmury wartości w modelach biznesów
PublicationObserwacja współczesnych metod tworzenia wartości daje podstawy do wyłonienia nowej logiki ich generowania. Analiza modeli wytwarzania wartości przez przedsiębiorstwa np. sieciowe wykazała, że formułują one chmury wartości. Struktury tych chmur są różnorodne, niejednolite, kłębiaste. Przeprowadzone prace pozwoliły na sformułowanie obrazów wartości generowanych przez twarde komponenty modeli biznesów. Osiągnięcie tych wyników pozwoliło...
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Metoda TrustCritic oceny wiarygodności sklepów internetowych
PublicationW artykule przedstawiono metodę oceny wiarygodności sklepów internetowych TrustCritic. Powszechnie występujące nadużycia w handlu elektronicznym sprawiają, że zaufanie do przedsiębiorcy staje się kluczowym czynnikiem decyzji konsumentów. Przedsiębiorca narażony jest na niezgodność z prawem, utratę wizerunku i klientów. Artykuł omawia problematykę nadużyć w sferze e-biznesu oraz proponuje wielokryterialny model oceny sklepu internetowego,...
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Analiza bibliometryczna w badaniach dotyczących prognozowania upadłości przedsiębiorstw w Polsce
PublicationCelem opracowania jest ukazanie obrazu piśmiennictwa poświęconego zagadnieniom prognozowania upadłości przedsiębiorstw w Polsce. Jako metodę badawczą zastosowano analizę bibliometryczną. Do analizy wykorzystano bazę Google Scholar oraz narzędzie Publish or Perish 7. Okresem badań objęto lata 1995– 2019. Jako frazy do wyszukiwania publikacji zastosowano: „prognozowanie upadłości”, „prognozowanie zagrożenia finansowego”, „systemy...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Electronic Noses in Medical Diagnostics
PublicationElectronic nose technology is being developed in order to identify aromas in a way parallel to the biologic olfaction. When applied to the field of medicine, such device should be able to identify and discriminate between different diseases. In recent years this kind of approach finds application in medical diagnostics, and especially in disease screening. Despite the fact that devices utilizing chemical sensor arrays are not routinely...
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Protokoły łączności do transmisji strumieni multimedialnych na platformie KASKADA
PublicationPlatforma KASKADA rozumiana jako system przetwarzania strumieni multimedialnych dostarcza szeregu usług wspomagających zapewnienie bezpieczeństwa publicznego oraz ocenę badań medycznych. Wydajność platformy KASKADA w znaczącym stopniu uzależniona jest od efektywności metod komunikacji, w tym wymiany danych multimedialnych, które stanowią podstawę przetwarzania. Celem prowadzonych prac było zaprojektowanie podsystemu komunikacji...
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Improving medical experts’ efficiency of misinformation detection: an exploratory study
PublicationFighting medical disinformation in the era of the pandemic is an increasingly important problem. Today, automatic systems for assessing the credibility of medical information do not offer sufficient precision, so human supervision and the involvement of medical expert annotators are required. Our work aims to optimize the utilization of medical experts’ time. We also equip them with tools for semi-automatic initial verification...
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Wykorzystanie analizy kosztów w zarządzaniu szpitalem publicznym
PublicationProblemy z finansowaniem opieki zdrowotnej obserwowane są praktycznie na całym świecie. Jako przyczyny wzrostu wydatków uważa się głównie starzenie się populacji, złożoną naturę współczesnych chorób i szerokie wykorzystywanie kosztownych technologii. Systemy opieki zdrowotnej na całym świecie stają przed trudnym wyzwaniem zwiększenia efektywności, co oznacza kontrolowanie kosztów, przy jednoczesnym zapewnieniu wysokiej jakości...
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Image Segmentation of MRI image for Brain Tumor Detection
Publicationthis research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...
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Driving the Image of an Electricity Supplier through Marketing Activities
PublicationThe aim of this study is to determine how marketing actions undertaken within the marketing mix by electricity providers influence their image. Referring to the Stimulus-Organism-Response (SOR) theory, research hypotheses were formulated, and a regression model was constructed, assuming positive impacts of selected marketing actions of electricity providers on their image. A quantitative approach was employed to test the research...
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Algorytmy wykrywania krawędzi w obrazie
PublicationWykrywanie krawędzi jest pierwszym etapem w cyfrowym przetwarzaniu obrazów. Operacja ta polega na usunięciu informacji takich jak kolor czy też jasność, a pozostawieniu jedynie krawędzi. Efektem tej operacji jest znaczna redukcja ilości danych do dalszej analizy. Pozwala to na zastosowanie w następnych etapach bardziej złożonych algorytmów rozpoznawania obiektów na podstawie kształtu. W artykule zaprezentowano zastosowanie algorytmów...
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On cooperative image denoising
PublicationIn this paper we suggest how several competing image denoising algorithms, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable denoising algorithm. The proposed fusion mechanism allows one to combine practically all kinds of noise reduction tools. It also allows one to account for the distribution of measurement noise, and in particular - to cope with heavy-tailed...