Laboratory image classification using di nwoye ephraim (6 risultati)

Paperback. Condizione: Brand New. 128 pages. 8.66x5.91x0.29 inches. In Stock.

Taschenbuch. Condizione: Neu. Laboratory Image Classification using Fuzzy Neural Algorithm: | Application for Colon Cancer Diagnosis | Ephraim Nwoye | Taschenbuch | 128 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659949135 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively. 128 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nwoye EphraimEphraim Nwoye holds a PhD in Electrical and ElectronicEngineering from the Newcastle University,United Kingdom andcurrently a professor of Biomedical Engineering at the University of Lagos, Nigeria with research interest.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Pathologists, daily, screen large numbers of slides containing cancerous cells manually. These are similar in shape, size or cells structure.This procedure or process then becomes arduous, difficult and can affect their judgement and decisions resulting in wrong diagnosis. Therefore development of an automated algorithmic approach, based on quantitative measurements, would be a valuable aid to the pathologist to verify abnormalities. The main aim of this book is therefore to use a neural network approach together with fuzzy arithmetic to establish a relationship between normal and cancer colon cell structures. This relationship is of high significance as it will result in an automated tool for accurate diagnosis. A novel Fast Fuzzy Neural Back-propagation Algorithm (FFNBA) for classification of colon cell images is therefore proposed. The algorithm used an optimal learning method for three layers MLP. The method automatically detects differences in biopsy images of the colorectal polyps, extracts the required image features and then classifies the cells into normal and cancer respectively.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.…