dr inż. Jan Cychnerski
Publikacje
Filtry
wszystkich: 40
Katalog Publikacji
-
Depth Images Filtering In Distributed Streaming
PublikacjaIn this paper, we propose a distributed system for point cloud processing and transferring them via computer network regarding to effectiveness-related requirements. We discuss the comparison of point cloud filters focusing on their usage for streaming optimization. For the filtering step of the stream pipeline processing we evaluate four filters: Voxel Grid, Radial Outliner Remover, Statistical Outlier Removal and Pass Through....
-
DEPTH IMAGES FILTERING IN DISTRIBUTED STREAMING
PublikacjaIn this paper we discuss the comparison of point cloud filters focusing on their applicability for streaming optimization. For the filtering stage within a stream pipeline processing we evaluate three filters: Voxel Grid, Pass Through and Statistical Outlier Removal. For the filters we perform series of the tests aiming at evaluation of changes of point cloud size and transmitting frequency (various fps ratio). We propose a distributed...
-
Towards Healthcare Cloud Computing
PublikacjaIn 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...
-
Automated Classifier Development Process for Recognizing Book Pages from Video Frames
PublikacjaOne of the latest developments made by publishing companies is introducing mixed and augmented reality to their printed media (e.g. to produce augmented books). An important computer vision problem that they are facing is classification of book pages from video frames. The problem is non-trivial, especially considering that typical training data is limited to only one digital original per book page, while the trained classifier...
-
Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
-
Real-Time Bleeding Detection in Gastrointestinal Tract Endoscopic Examinations Video
PublikacjaThe article presents a novel approach to medical video data analysis and recognition of bleedings. Emphasis has been put on adapting pre-existing algorithms dedicated to the detection of bleedings for real-time usage in a medical doctor’s office during an endoscopic examination. A real-time system for analyzing endoscopic videos has been designed according to the most significant requirements of medical doctors. The main goal of...
-
Real-Time Gastrointestinal Tract Video Analysis on a Cluster Supercomputer
PublikacjaThe article presents a novel approach to medical video data analysis and recognition. Emphasis has been put on adapting existing algorithms detecting le- sions and bleedings for real time usage in a medical doctor's office during an en- doscopic examination. A system for diagnosis recommendation and disease detec- tion has been designed taking into account the limited mobility of the endoscope and the doctor's requirements. The...
-
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...
-
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...
-
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...
-
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.
-
Clothes Detection and Classification Using Convolutional Neural Networks
PublikacjaIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
-
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...
-
A Regular Expression Matching Application with Configurable Data Intensity for Testing Heterogeneous HPC Systems
PublikacjaModern High Performance Computing (HPC) systems are becoming increasingly heterogeneous in terms of utilized hardware, as well as software solutions. The problems, that we wish to efficiently solve using those systems have different complexity, not only considering magnitude, but also the type of complexity: computation, data or communication intensity. Developing new mechanisms for dealing with those complexities or choosing an...
-
Data Mining Applications and Methods in Medicine
PublikacjaIn this paper we describe the research area of data mining and its applications in medicine. The origins of data mining and its crucial features are shortly presented. We discuss the specificity of medicine as an application area for computer systems. Characteristic features of the medical data are investigated. Common problems in the area are also presented as well as the strengths and capabilities of the data mining methods....
-
ANYTIME POLYNOMIAL HEURISTIC ALGORITHM FOR PARTITIONING GROUPS OF DATA WITH PRESERVING CLASS PROPORTIONS FOR CROSS-VALIDATION
PublikacjaThe article describes a problem of splitting data for k-fold cross-validation, where class proportions must be preserved, with additional constraint that data is divided into groups that cannot be split into different cross-validation sets. This problem often occurs in e.g. medical data processing, where data samples from one patient must be included in the same cross-validation set. As this problem is NP-complete, a heuristic...
-
AN ALGORITHM FOR PORTAL HYPERTENSIVE GASTROPATHY RECOGNITION ON THE ENDOSCOPIC RECORDINGS
PublikacjaSymptoms recognition of portal hypertensive gastropathy (PHG) can be done by analysing endoscopic recordings, but manual analysis done by physician may take a long time. This increases probability of missing some symptoms and automated methods may be applied to prevent that. In this paper a novel hybrid algorithm for recognition of early stage of portal hypertensive gastropathy is proposed. First image preprocessing is described....
-
Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublikacjaThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
-
Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
-
Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublikacjaThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
wyświetlono 1412 razy