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Benign/Malignant Tissues Classification
Details
Breast cancer has become a major health problem over the last 50 years; it is a leading cause of cancer-related death in women population today. However, if breast abnormalities are detected and diagnoses are made at early stages, studies show that the chances of survival can be greatly improved. In this work, multi-scale fractal dimension is used to derive a set of textural features in order to perform texture analysis on breast tissues samples. The box counting method was used to estimate the multi fractal dimensions. The feed forward neural network is used to classify different types of breast tissues according to the extracted fractal dimension vectors.
Autorentext
B.Sc. in Computer Science, University of Mosul, Iraq, M.Sc. and Ph.D. in Computer Science, University of Sulaimani, Iraq. Research interests:Artificial Neural networks, CBIR, Database, Fractals, FPGA, Image Processing, Wireless Communication.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783659328152
- Sprache Englisch
- Genre Anwendungs-Software
- Größe H220mm x B150mm x T7mm
- Jahr 2013
- EAN 9783659328152
- Format Kartonierter Einband
- ISBN 3659328154
- Veröffentlichung 07.02.2013
- Titel Benign/Malignant Tissues Classification
- Autor Esraa Zeki Mohammed , Loay Edwar George
- Untertitel Methods,Concepts and System for Tissue Recognition
- Gewicht 185g
- Herausgeber LAP LAMBERT Academic Publishing
- Anzahl Seiten 112