Supervised Segmentation of the Cervical Cell Images by Using the Genetic Algorithms.
Nadia LassouaouiLatifa HamamiFairouz ChehbourPublished in: IWANN (2) (2003)
Keyphrases
- microscopy images
- microscopic images
- segmentation method
- segmentation algorithm
- confocal images
- image analysis
- cell segmentation
- genetic algorithm
- test images
- microscope images
- image regions
- fluorescence microscopy images
- segmentation errors
- segmentation accuracy
- cell nuclei
- grey level
- fully automatic
- image classification
- object recognition
- spinal cord
- edge detection
- image database
- input image
- tubular structures
- white blood
- accurate segmentation
- unsupervised segmentation
- image slices
- pixel wise
- image features
- region growing
- image data
- object segmentation
- multiple objects
- three dimensional
- segmented images
- image segmentation
- intensity images
- ground truth
- cancer cells
- adaptive thresholding
- low depth of field
- white blood cells
- cell nucleus
- neural network
- image registration
- positron emission tomography
- image segments
- shape prior
- bounding box
- low contrast
- segmentation result
- foreground and background