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Wyszukujesz frazę "Rough sets" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
Partial volume effect detection in MRI segmentation based on approximate decision reducts
Autorzy:
Widz, S.
Powiązania:
https://bibliotekanauki.pl/articles/333876.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
segmentacja obrazów MRI
PVE
zbiory przybliżone
MRI Segmentation
rough sets
approximate decision reducts
Opis:
Segmentation of Magnetic Resonance Imaging (MRI) is a process of assigning tissue class labels to voxels. One of the main sources of segmentation error is the partial volume effect (PVE) which occurs most often with low resolution images - with large voxels, the probability of a voxel containing multiple tissue classes increases. We propose a multistage algorithm for segmenting MRI images with a mid-stage of recognizing the PVE voxels. The information about PVE regions added to other voxels features extracted from the image can increase the overall accuracy of the segmentation. In our methods we have utilize a classification approach based on approximate decision reducts derived from the data mining paradigm of the theory of rough sets. An approximate reduct is an irreducible subset of features, which enables to classify decision concepts with a satisfactory degree of accuracy in the training data. The ensembles of best found reducts trained for appropriate approximation degrees are applied to detection of the PVE and performing the segmentation.
Źródło:
Journal of Medical Informatics & Technologies; 2007, 11; 227-233
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rough sets in identification of cellular automata for medical image processing
Autorzy:
Płaczek, B.
Powiązania:
https://bibliotekanauki.pl/articles/333253.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
rough sets
cellular automata
medical image processing
zbiory przybliżone
automaty komórkowe
przetwarzanie obrazów medycznych
Opis:
In this paper a method is proposed which enables identification of cellular automata (CA) that extract low-level features in medical images. The CA identification problem includes determination of neighbourhood and transition rule on the basis of training images. The proposed solution uses data mining techniques based on rough sets theory. Neighbourhood is detected by reducts calculations and rule-learning algorithms are applied to induce transition rules for CA. Experiments were performed to explore the possibility of CA identification for boundary detection, convex hull transformation and skeletonization of binary images. The experimental results show that the proposed approach allows finding CA rules that are useful for extraction of specific features in microscopic images of blood specimens.
Źródło:
Journal of Medical Informatics & Technologies; 2013, 22; 161-168
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Models of computational intelligence in bioinformatics
Autorzy:
Pedrycz, W.
Powiązania:
https://bibliotekanauki.pl/articles/333235.pdf
Data publikacji:
2003
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
obliczenia granularne
logika
bioinformatyka
granulki informacji
zbiory rozmyte
zbiory przybliżone
granular computing
logics
bioinformatics
information granules
fuzzy sets
rough sets
Opis:
Computational Intelligence has emerged as a synergistic environment of Granular Computing (including fuzzy sets, rough sets, interval analysis), neural networks and evolutionary optimisation. This symbiotic framework addresses the needs of system modelling with regard to its transparency, accuracy and user friendliness. This becomes of paramount interest in various modelling in bioinformatics especially when we are concerned with decision-making processes. The objective of this study is to elaborate on the two essential features of CI that is Granular Computing and the resulting aspects of logic-oriented processing and its transparency. As the name stipulates, Granular Computing is concerned with processing carried out at a level of coherent conceptual entities - information granules. Such granules are viewed as inherently conceptual entities formed at some level of abstraction whose processing is rooted in the language of logic (especially, many valued or fuzzy logic). The logic facet of processing is cast in the realm of fuzzy logic and fuzzy sets that construct a consistent processing background necessary for operating on information granules. Several main categories of logic processing units (logic neurons) are discussed that support aggregative (and-like and or-like operators) and referential logic mechanisms (dominance, inclusion, and matching). We show how the logic neurons contribute to high functional transparency of granular processing, help capture prior domain knowledge and give rise to a diversity of the resulting models.
Źródło:
Journal of Medical Informatics & Technologies; 2003, 5; IP13-23
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nondeterministic decision rules in classification process for medical data
Autorzy:
Marszał-Paszek, B.
Paszek, P.
Powiązania:
https://bibliotekanauki.pl/articles/333507.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
niedeterministyczne reguły decyzyjne
klasyfikacja
tablice decyzyjne
zbiory przybliżone
zasada klasyfikatora
nondeterministic decision rules
classification
decision tables
rough sets
rule-based classifiers
Opis:
In the paper, we discuss nondeterministic rules in decision tables, called the second type nondeterministic rules. They have a few decisions values on the right hand side but on the left hand side only one attribute that has two values. We show that these kinds of rules can be used for improving the quality of classification. It is important in rule-based diagnosis support systems, where classification error can lead to serious consequences. The well known greedy strategy to construct the new nondeterministic rules, have been proposed. Additionally, based on deterministic and nondeterministic (second type) rules, classification algorithm with polynomial computational complexity has been developed. This rule-based classifier was tested on the group of decision tables, containing medical data, from the UCI Machine Learning Repository. The reported results of experiments showing that by combining rule-based classifier based on deterministic rules with second type nondeterministic rules give us possibility to improve the classification quality.
Źródło:
Journal of Medical Informatics & Technologies; 2011, 17; 59-64
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Deterministic and nondeterministic decision rules in classification process
Autorzy:
Paszek, P.
Marszał-Paszek, B.
Powiązania:
https://bibliotekanauki.pl/articles/333940.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
klasyfikacja
tablice decyzyjne
niedeterministyczne reguły decyzyjne
zbiory przybliżone
zasada klasyfikatora
classification
decision tables
nondeterministic decision rules
rough sets
rule-based classifiers
Opis:
In this paper an algorithm of calculating nondeterministic decision rules from the decision table was presented. The algorithm uses additional conditions imposed on rules. This is a greedy algorithm. The nondeterministic decision rules were used in the process of classification of new examples, for medical data sets. The decision tables from the UCI Machine Learning Repository were used. The achieved results allow us to state that nondeterministic decision rules can be used for improving the quality of classification.
Źródło:
Journal of Medical Informatics & Technologies; 2010, 15; 87-92
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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