dr inż. Jan Cychnerski
Publikacje
Filtry
wszystkich: 40
Katalog Publikacji
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Comparison of image pre-processing methods in liver segmentation task
PublikacjaAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
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Architecture Design of a Networked Music Performance Platform for a Chamber Choir
PublikacjaThis paper describes an architecture design process for Networked Music Performance (NMP) platform for medium-sized conducted music ensembles, based on remote rehearsals of Academic Choir of Gdańsk University of Technology. The issues of real-time remote communication, in-person music performance, and NMP are described. Three iterative steps defining and extending the architecture of the NMP platform with additional features to...
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Semantic segmentation training using imperfect annotations and loss masking
PublikacjaOne 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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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
PublikacjaDeployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the...
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MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublikacjaWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
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Algorytmy rozpoznawania zmian chorobowych
PublikacjaW pracy przedstawiono, opisano i porównano pod wzgledem skutecznosci wybrane algorytmy rozpoznawania chorób w filmach endoskopowych, zaimplementowane w ramach aplikacji Wspomagania Badan Medycznych. Dokonano oceny algorytmów w zaawansowanym srodowisku testowym, zbudowanym w oparciu o duzy zbiór obrazów z filmów endoskopowych, pozyskanych we współpracy z Gdanskim Uniwersytetem Medycznym. Jednoczesnie zaprezentowano sposób optymalizacji...
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METHOD OF TRAINING THE ENDOSCOPIC VIDEO ANALYSIS ALGORITHMS TO MAXIMIZE BOTH ACCURACY AND STABILITY
PublikacjaIn the article a new training and testing method of endoscopic video analysis algorithms is presented. Classical methods take into account only eciency of recognizing objects on single video frames. Proposed method additionally considers stability of classiers output for real video input. The method is simple and can be trained on data sets created for other solutions. Therefore, it is easily applicable to existing endoscopic video...
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ISSUES OF CLASSIFICATION FUNCTION CONTINUITY IN ENDOSCOPIC VIDEO CLASSIFICATION
PublikacjaIn the article a new way of analyzing the properties of feature vector functions (FVF) and classiers of images in a video stream is proposed. The general idea is based on focusing of the perceived continuity of the FVF and classier functions. Issues related to creating an exact mathematical model are discussed and a simplied solution is proposed. An exemplary algorithm is evaluated on three exemplary video sequences. The acquired...
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Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublikacjaIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
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Endoscopic Videos Deinterlacing and On-Screen Text and Light Flashes Removal and Its Influence on Image Analysis Algorithms' Efficiency
PublikacjaIn this article, deinterlacing and removing on- screen text and light flashes methods on endoscopic video images are discussed. The research is intended to improve disease recognition algorithms' performance. In the article, four configurations of deinterlacing methods and another four configurations of text and flashes removal methods are described and examined. The efficiency of endoscopic video analysis algorithms is measured...
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Tworzenie i wykorzystanie bazy wzorców zmian chorobowych
PublikacjaPrzedstawiono bazy danych zbudowane na potrzeby systemu wspomagania badan medycznych oraz aplikacje je wykorzystujace. Szczególna uwaga poswiecona została bazie danych wzorców medycznych, której rozmiar czyni ja jedna z wiekszych baz stosowanych w dziedzinie. Artykuł zawiera obszerny przeglad zgromadzonych w bazie przypadków chorobowych, zestawionych według rodzajów schorzen oraz według miejsca wystapienia schorzenia. Konstrukcja...
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PERFORMANCE OF ENDOSCOPIC IMAGE ANALYSIS ALGORITHMS IN LARGE BOWEL VIDEOS PROCESSING
PublikacjaComputer-assisted endoscopy is a rapidly developing eld of study. Many image anal- ysis algorithms exist, achieving very high rates of eciency at processing single endoscopic images. However, most of them were never tested in processing real-life endoscopic videos. In the article such tests of 16 endoscopy image analysis algorithms are presented and dis- cussed. Tests were performed on two real-life endoscopic videos of a human...
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Aplikacja MedEye dla diagnostyki układu pokarmowego
PublikacjaOmówiono problematyke badan endoskopowych za pomoca endoskopii kapsułkowej. Zaprezentowano główne komponenty oraz zakres funkcjonalnosci aplikacji MedEye, wspomagajacej tego typu diagnostyke. Na podstawie subiektywnych ocen lekarzy wyciagnieto ogólne wnioski na temat przydatnosci poszczególnych jej elementów. W podsumowaniu opisano perspektywy jej rozwoju i wdrozenia w srodowisku medycznym.
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An Overview of Image Analysis Techniques in Endoscopic Bleeding Detection
PublikacjaAuthors review the existing bleeding detection methods focusing their attention on the image processing techniques utilised in the algorithms. In the article, 18 methods were analysed and their functional components were identified. The authors proposed six different groups, to which algorithms’ components were assigned: colour techniques, reflecting features of pixels as individual values, texture techniques, considering spatial...
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Konstrukcja bazy danych dla systemu wspomagania diagnostyki chorób przewodu pokarmowego
PublikacjaW artykule krótko przedstawiono charakterystykę procesu diagnostyki chorób przewodu pokarmowego oraz istniejące techniki wspomagania go na bazie analizy zdjęć z badań endoskopowych. Szczegółowo opisano proces tworzenia specjalistycznej bazy danych medycznych, której przeznaczeniem jest wspomaganie procesu uczenia klasyfikatorów chorób przewodu pokarmowego. Na koniec przedstawiono zebrane w bazie dane oraz uzyskane efekty.
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Endoscopic Video Classification with the Consideration of Temporal Patterns
PublikacjaThe article describes a novel approach to automatic recognition and classification of diseases in endoscopic videos. Current directions of research in this field are discussed. Most presented methods focus on processing single frames and do not take into consideration the temporal relationship between continuous classifications. Existing approaches that consider the temporal structure of an incoming frame sequence are focused on...
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Contour Analysis of Bleeding Regions in Endoscopic Images
PublikacjaThis paper investigates the problem of detecting bleeding regions in images acquired from endoscopic examinations of gastrointestinal tract. The purpose is to identify the characteristic features of bleeding areas' contours in order to develop an accurate method for discriminating between true bleeding regions and missed detections, which could lead to a significant reduction of the false alarm rate of existing blood-detection...
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An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublikacjaThe 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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Dependable Integration of Medical Image Recognition Components
PublikacjaComputer driven medical image recognition may support medical doctors in the diagnosis process, but requires high dependability considering potential consequences of incorrect results. The paper presentsa system that improves dependability of medical image recognition by integration of results from redundant components. The components implement alternative recognition algorithms of diseases in thefield of gastrointestinal endoscopy....
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