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Wyszukujesz frazę "pattern analysis" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Nuclei segmentation for computer-aided diagnosis of breast cancer
Autorzy:
Kowal, M.
Filipczuk, P.
Powiązania:
https://bibliotekanauki.pl/articles/330248.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
computer aided diagnosis
breast cancer
pattern analysis
fast marching
diagnostyka wspomagana komputerowo
rak piersi
analiza obrazu
Opis:
Breast cancer is the most common cancer among women. The effectiveness of treatment depends on early detection of the disease. Computer-aided diagnosis plays an increasingly important role in this field. Particularly, digital pathology has recently become of interest to a growing number of scientists. This work reports on advances in computer-aided breast cancer diagnosis based on the analysis of cytological images of fine needle biopsies. The task at hand is to classify those as either benign or malignant. We propose a robust segmentation procedure giving satisfactory nuclei separation even when they are densely clustered in the image. Firstly, we determine centers of the nuclei using conditional erosion. The erosion is performed on a binary mask obtained with the use of adaptive thresholding in grayscale and clustering in a color space. Then, we use the multi-label fast marching algorithm initialized with the centers to obtain the final segmentation. A set of 84 features extracted from the nuclei is used in the classification by three different classifiers. The approach was tested on 450 microscopic images of fine needle biopsies obtained from patients of the Regional Hospital in Zielona Góra, Poland. The classification accuracy presented in this paper reaches 100%, which shows that a medical decision support system based on our method would provide accurate diagnostic information.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 1; 19-31
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automatic detection and counting of platelets in microscopic image
Autorzy:
Burduk, R.
Krawczyk, B.
Powiązania:
https://bibliotekanauki.pl/articles/333065.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
nauczanie maszynowe
analiza obrazu
pattern recognition
bioinformatic
machine learning
image analysis
platelet
Opis:
In this paper we present a machine learning-based approach for detecting platelet cells in microscopic smear images. Counting how many platelets appeared in each smear image is one of the basic tasks done in many laboratories. In many cases this is still done by a human — laboratory technician. Due to very small size and often great quantity of those cells, precise estimating of the number of platelets is not a trivial task. As in all man-dependent problems the whole process is very sensitive to errors, time-consuming and its accuracy is limited by human perception. We propose alternative, fully automatic solution that is free of those drawbacks. Our idea is based on the combination of techniques driven from two fields of modern computer science: the image analysis and pattern recognition ⁄ machine learning. It not only reduces the error rate, but, what is more important, also decreases the time needed for each smear image analysis. The obtained results are very satisfying and our solution is more precise than estimation based on human perception. This will improve the quality of laboratory work and allow to save time that can be spent on other important tasks.
Źródło:
Journal of Medical Informatics & Technologies; 2010, 16; 173-178
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Local embedding and dimensionality reduction in detection of skin tumor tissue
Autorzy:
Michalak, M.
Świtoński, A.
Powiązania:
https://bibliotekanauki.pl/articles/333429.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
analiza wielospektralna
redukcja wymiarowości
selekcja cech
pattern recognition
multispectral analysis
dimensionality reduction
feature selection
Opis:
This article shows the limitation of the usage of dimensionality reduction methods. For this purpose three algorithms were analyzed on the real medical data. This data are multispectral images of human skin labeled as tumor or non-tumor regions. The classification of new data required the special algorithm of new data mapping that is also described in the paper. Unfortunately, the final conclusion is that this kind of local embedding algorithms should not be recommended for this kind of analysis and prediction.
Źródło:
Journal of Medical Informatics & Technologies; 2012, 19; 59-65
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Detection of human eye components on the basis of multispectral imaging
Autorzy:
Michalak, M.
Nurzyńska, K.
Świtoński, A.
Powiązania:
https://bibliotekanauki.pl/articles/333415.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rozpoznawanie wzorców
analiza wielospektralna
przetwarzanie obrazów
segmentacja obrazu
pattern recognition
multispectral analysis
image processing
image segmentation
Opis:
In this paper the methods for selecting of the most important parts of the human eyes are described. On the basis of the real 21 channel multispectral images the model of finding the lens and the spot are defined. These methods are based on the most popular algorithms of image processing. The approach to veins detection is still undefined but in the article the most important channels are pointed out and the channel difference between eyelash and the veins is also mentioned.
Źródło:
Journal of Medical Informatics & Technologies; 2012, 19; 41-47
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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