Segmentation and classification of two-channel C. elegans nucleus-labeled fluorescence images.
Mengdi ZhaoJie AnHaiwen LiJiazhi ZhangShang-Tong LiXue-Mei LiMeng-Qiu DongHeng MaoLouis TaoPublished in: BMC Bioinform. (2017)
Keyphrases
- image analysis
- manual labeling
- pigmented skin lesions
- microscope images
- segmentation method
- image classification
- segmentation algorithm
- test images
- cell nuclei
- segmented images
- image regions
- edge detection
- segmentation errors
- image data
- ground truth
- fully automatic
- input image
- image features
- adaptive thresholding
- skin lesion
- accurate segmentation
- cell nucleus
- three dimensional
- image retrieval
- object recognition
- grey level
- white blood cells
- image segmentation
- multiscale
- segmentation accuracy
- image registration
- multiple objects
- supervised learning
- microscopy images
- textural features
- training set
- image segmentation algorithms
- feature extraction
- feature vectors
- level set
- object segmentation
- region growing
- feature selection
- correct classification
- labeling process
- automatic segmentation
- text classification