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dr inż. Magdalena Mazur-Milecka
Employment
- Assistant professor at Department of Biomedical Engineering
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total: 17
Catalog Publications
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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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Automatic analysis of the aggressive behavior of laboratory animals using thermal video processing
PublicationThe bite detection is very important but difficult element of the social interaction analysis. Standard observation methods like human observer or a camcorder of visible light frequencies fail in this case. However, it is possible to discern cooler spots on the rodent's body that appear after body contact with another individual, and vanish after short time. These spots are assumed to be a saliva trace left on fur after bite. In...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Smart city and fire detection using thermal imaging
PublicationIn this paper, we summarize the results obtained from fire experiments. The aim of the work was to develop new methods of fire detection using IR thermal imaging cameras and dedicated image processing. We conducted 4 experiments in different configurations and with the use of different objects. The conducted experiments have shown the great usefulness of infrared cameras for detecting the seeds of a fire. Even cheap low-resolution...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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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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The analysis of temperature changes of the saliva traces left on the fur during laboratory rats social contacts
PublicationAutomatic analysis of complex rodent social be- havior, especially aggressive ones, is of important scientific interest. In this paper we analyze the properties of the data created as a result of aggressive rodent social behavior. Detec- tion of specific aggressive behaviors is based on the event of leaving traces of saliva on the fur of the attacked individual, which are clearly visible in the thermal imaging. The traces change...
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Detection of the Oocyte Orientation for the ICSI Method Automation
PublicationAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...
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Thermal imaging in automatic rodent’s social behaviour analysis
PublicationLaboratory rodent social behaviour analysis is an extremely important task for biological, medical and pharmacological researches. In this work thermal images features that facilitate analysis are presented. Methods to distinguish objects on the basis of thermal distribution are tested. Actions of grooming or biting one rodent by another - important social behaviour incidents - are clearly visible...
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Detection and Model of Thermal Traces Left after Aggressive Behavior of Laboratory Rodents
PublicationAutomation of complex social behavior analysis of experimental animals would allow for faster, more accurate and reliable research results in many biological, pharmacological, and medical fields. However, there are behaviors that are not only difficult to detect for the computer, but also for the human observer. Here, we present an analysis of the method for identifying aggressive behavior in thermal images by detecting traces...
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Analiza możliwości automatycznego rozpoznawania zachowań zwierząt doświadczalnych
PublicationAutomatyzacja analizy zachowań zwierząt laboratoryjnych umożliwia szybką i obiektywną ocenę obserwacji. Rozwiązania w istniejących systemach skupiają się na detekcji prostych aspektów zachowań, która jest możliwa dzięki pomiarowi parametrów motorycznych zwierząt, ich punktów charakterystycznych czy kształtu ciała. Jednym z istotnych problemów w dziedzinie rozpoznania zachowań są zachowania złożone, dla których trudno jest zdefiniować...
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Comparison of Tracking Methods in Respect of Automation of Animal Behavioral Test
PublicationAutomation in experiments carried out on animals is getting more and more important in research. Computers take over laborious and time-consuming activities like recording and analysing images of experiment scene. The first step in an image analysis is finding and distinguishing between the observed animals, and then tracking all objects during the experiment. In this paper four tracking methods are presented. Quantitative and...
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An automated aystem for analysis of mouse movement activity
Publication.
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Ensembling noisy segmentation masks of blurred sperm images
PublicationBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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