Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip.
Nianyin ZengHan LiZidong WangWeibo LiuSongming LiuFuad E. AlsaadiXiaohui LiuPublished in: Neurocomputing (2021)
Keyphrases
- quantitative analysis
- cell segmentation
- cell nuclei
- segmentation algorithm
- reinforcement learning
- image analysis
- segmentation method
- qualitative analysis
- segmented images
- test images
- segmentation errors
- edge detection
- qualitative evaluation
- accurate segmentation
- ground truth
- image database
- fully automatic
- pixel wise
- cancer cells
- quantitative evaluation
- pixel level
- input image
- image segmentation
- image regions
- brain structures
- segmentation accuracy
- microscope images
- brain mr images
- tubular structures
- image data
- automatically segmented
- image segmentation algorithms
- grey level
- image features
- segmentation result
- qualitative and quantitative analysis
- region growing
- image registration
- adaptive thresholding
- image retrieval
- pigmented skin lesions
- image segments
- watershed transform
- intensity distribution
- multiple objects
- mr images