Improvement of features extraction process and classification of Cervical cancer for the NeuralPap system

Improvement of features extraction process and classification of Cervical cancer for the NeuralPap system

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Cervical cancer has caused many deaths each year. Screening tests, such as Pap smear test used for the detection of the precancerous stage are able to avoid the occurrence of cervical cancer. However, the Pap smear test has several disadvantages such as less effective slides preparation and human er...

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Bibliographic Details
Main Authors: Ahmad, F. (Author), Ding L. (Author), Howlett R.J (Author), Jain L.C (Author), Leong M.K (Author), Mat-Isa, N.A (Author), Othman, N.H (Author), Pang C. (Author), Sulaiman, S.N (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2015
Subjects:
Algorithms
Cervical cancer
Cervical cancers
Clustering algorithm
Clustering algorithms
Computer aided diagnosis
Computer aided diagnosis systems
Cytology
Diagnosis system
Diagnosis systems
Diseases
Extraction
Feature extraction
Feature extraction algorithms
Image processing
Image processing algorithm
Image segmentation
Knowledge based systems
Neural network
Neural networks
Positioning algorithms
Radial basis function networks
Radial Basis Function(RBF)
Region growing
Region Growing
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