Mixture of learners for cancer stem cell detection using CD13 and H and E stained images.
Oguzhan OguzCem Emre AkbasMaen MallahKasim TasdemirEce Akhan GüzelcanChristian MünzenmayerThomas WittenbergAysegül ÜnerA. Enis ÇetinRengül Çetin-AtalayPublished in: Medical Imaging: Digital Pathology (2016)
Keyphrases
- image data
- stem cell
- image analysis
- image retrieval
- input image
- microscopic images
- image database
- ground truth
- automatic detection
- image features
- object recognition
- lymph nodes
- detection rate
- object detection
- three dimensional
- image registration
- edge detection
- image classification
- traffic signs
- learning environment
- digitized images
- automated detection
- early detection
- bounding box
- image regions
- learning experience
- detection algorithm
- video sequences
- learning styles
- cell nuclei
- cancer cells
- segmentation algorithm
- microscopy images
- test images
- gray level
- computer vision
- learning process
- e learning