Classification of Cervical-Cancer Using Pap-Smear Images: A Convolutional Neural Network Approach.
Bilal TahaJorge DiasNaoufel WerghiPublished in: MIUA (2017)
Keyphrases
- cervical cancer
- convolutional neural network
- image classification
- input image
- image database
- three dimensional
- ground truth
- pattern recognition
- test images
- hyperspectral images
- image analysis
- classification accuracy
- image data
- image retrieval
- image registration
- computer aided diagnosis
- extracted features
- object recognition
- decision trees
- training set
- machine learning
- image collections
- image set
- neural network
- computer aided
- face detection
- microscope images
- feature extraction
- edge detection
- feature vectors
- skin lesion
- preprocessing stage
- thematic mapper
- pigmented skin lesions
- low contrast
- gabor filters
- region of interest
- image regions
- support vector machine svm
- text categorization
- text classification
- similarity measure
- image processing
- computer vision