Automatic cytoplasm and nuclei segmentation for color cervical smear image using an efficient gap-search MRF.
Lili ZhaoKuan LiMao WangJianping YinEn ZhuChengkun WuSiqi WangChengzhang ZhuPublished in: Comput. Biol. Medicine (2016)
Keyphrases
- confocal images
- microscopy images
- segmentation method
- image segmentation
- image regions
- markov random field
- microscopic images
- energy function
- region growing
- mrf model
- images of natural scenes
- segmentation algorithm
- textured images
- homogeneous regions
- grey level
- image analysis
- gray level images
- color segmentation
- color image segmentation
- color features
- color model
- test images
- image data
- low level vision
- gray value
- gradient information
- multiscale
- foreground and background
- single image
- input image
- prior model
- image features
- color images
- fully automatic
- color correction
- graph cuts
- salient regions
- image pixels
- pixel level
- edge detection
- outdoor scenes
- random fields
- color space
- complex background
- image preprocessing
- pixel values
- pixel classification
- segmentation scheme
- color and texture information
- histogram analysis
- image content
- segmented images
- pairwise
- hsv color space
- color information
- color components
- watershed transform
- gray level
- microscope images
- white blood cells
- mrf models
- image retrieval
- color distribution
- fundamental problem in computer vision
- shape prior
- higher order
- active contours
- watershed segmentation
- contrast enhancement