Sipakmed: A New Dataset for Feature and Image Based Classification of Normal and Pathological Cervical Cells in Pap Smear Images.
Marina E. PlissitiPanagiotis DimitrakopoulosGiorgos SfikasChristophoros NikouO. KrikoniAntonia CharchantiPublished in: ICIP (2018)
Keyphrases
- image classification
- image features
- microscopy images
- microscope images
- feature set
- feature vectors
- discriminative features
- feature representation
- image data
- preprocessing stage
- input image
- dissimilarity representation
- decision trees
- blood cells
- benchmark datasets
- image database
- image dataset
- cancer cells
- cervical cancer
- handwritten digits
- image registration
- spinal cord
- image collections
- classification accuracy
- image analysis
- test images
- gray level co occurrence matrix
- three dimensional
- cell nuclei
- feature space
- image retrieval
- outdoor images
- feature extraction
- segmentation algorithm
- similarity measure
- textural features
- object recognition
- text classification
- thematic mapper
- training set
- pigmented skin lesions
- feature selection
- training data
- skin lesion
- photo collections
- early detection
- image annotation
- image set
- image matching
- edge detection
- support vector machine