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Search results for: medical image classification
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599721941]
Open Research DataThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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Adrenal gland, unspecified - Male, 1 - Tissue image [7220729599721221]
Open Research DataThis is the histopathological image of ADRENAL GLAND tissue sample obtained in Medical University Gdańsk and deposited in ZMDL-GUMED. The sample image was taken using: Pannoramic 250 3DHistech slide scanner (20x magnification) and saved to DICOM format.
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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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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Multi-Aspect Quality Assessment Of Mobile Image Classifiers For Companion Applications In The Publishing Sector
PublicationThe paper presents the problem of quality assessment of image classifiers used in mobile phones for complimentary companion applications. The advantages of using this kind of applications have been described and a Narrator on Demand (NoD) functionality has been described as one of the examples, where the application plays an audio file related to a book page that is physically in front of the phone's camera. For such a NoD application,...
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A survey of automatic speech recognition deep models performance for Polish medical terms
PublicationAmong the numerous applications of speech-to-text technology is the support of documentation created by medical personnel. There are many available speech recognition systems for doctors. Their effectiveness in languages such as Polish should be verified. In connection with our project in this field, we decided to check how well the popular speech recognition systems work, employing models trained for the general Polish language....
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Agnieszka Mikołajczyk-Bareła dr inż.
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublicationThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Seafloor characterisation using multibeam sonar echo signal processing and image analysis
PublicationThe authors propose the approach to multibeam seafloor characterisation which relies on the combined, concurrent use of two different techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the echoes received in the consecutive beams. Then, the parameters describing the local region of sonar image, namely, the local standard deviation of a grey level, and...
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A System for Heart Sounds Classification
PublicationThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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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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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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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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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublicationThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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Market Structure and Market Power in Selected Sectors of The Polish Economy Based on COICOP Classification
PublicationThis paper present new and simple measures of market structure and market power. Based on the classical models of market structures, where a given structure is determined by the number of enterprises, indexes of degree of monopoly have been estimated, representing an average number of entities per branch. Additionally, market power indexes have been determined as an average revenue per an enterprise in a given branch. This approach...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublicationThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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On Algorithm Details in Multibeam Seafloor Classification
PublicationRemote sensing of the seafloor constitutes an important topic in exploration, management, protection and other investigations of the marine environment. In the paper, a combined approach to seafloor characterisation is presented. It relies on calculation of several descriptors related to seabed type using three different types of multibeam sonar data obtained during seafloor sensing, viz.: 1) the grey-level sonar images (echograms)...
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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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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Towards Healthcare Cloud Computing
PublicationIn this paper we present construction of a software platform for supporting medical research teams, in the area of impedance cardiography, called IPMed. Using the platform, research tasks will be performed by the teams through computer-supported cooperative work. The platform enables secure medical data storing, access to the data for research group members, cooperative analysis of medical data and provide analysis supporting tools...
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Mask Detection and Classification in Thermal Face Images
PublicationFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
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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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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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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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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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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Automatic classification and mapping of the seabed using airborne LiDAR bathymetry
PublicationShallow coastal areas are among the most inhabited areas and are valuable for biodiversity, recreation and the economy. Due to climate change and sea level rise, sustainable management of coastal areas involves extensive exploration, monitoring, and protection. Current high-resolution remote sensing methods for monitoring these areas include bathymetric LiDAR. Therefore, this study presents a novel methodological approach to assess...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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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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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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Marta Kuc-Czarnecka dr
PeopleMarta Kuc-Czarnecka is the deputy head of the Department of Statistics and Economics at the Faculty of Management and Economics of the Gdańsk University of Technology. She also serves as the Dean's proxy for AMBA accreditation. She is a co-founder of Rethinking Economics Gdańsk and a member of the Foundation Edward Lipiński for the promotion of pluralism in economic sciences. In 2018-2022, she was Eurofound’s quality of life and...
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LEGO bricks for training classification network
Open Research DataThe data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...
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Spike patterns and chaos in a map-based neuron model
PublicationThe work studies the well-known map-based model of neuronal dynamics introduced in 2007 by Courbage, Nekorkin and Vdovin, important due to various medical applications. We also review and extend some of the existing results concerning β-transformations and (expanding) Lorenz mappings. Then we apply them for deducing important properties of spike-trains generated by the CNV model and explain their implications for neuron behaviour....
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Improving automatic surveillance by sound analysis
PublicationAn automatic surveillance system, based on event detection in the video image can be improved by implementing algorithms for audio analysis. Dangerous or illegal actions are often connected with distinctive sound events like screams or sudden bursts of energy. A method for detection and classification of alarming sound events is presented. Detection is based on the observation of sudden changes in sound level in distinctive sub-bands...
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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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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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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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Visual Attention Distribution Based Assessment of User's Skill in Electronic Medical Record Navigation
PublicationCurrently, the most precise way of reflecting the skills level is an expert’s subjective assessment. In this paper we investigate the possibility of the use of eye tracking data for scalar quantitative and objective assessment of medical staff competency in EMR system navigation. According to the experiment conducted by Yarbus the observation process of particular features is associated with thinking. Moreover, eye tracking is...
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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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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublicationIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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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...