Automated end-to-end deep learning framework for classification and tumor localization from native non-stained pathology images.
Akram BayatConnor AndersonPratik ShahPublished in: Medical Imaging: Image Processing (2021)
Keyphrases
- end to end
- text localization and recognition
- deep learning
- image classification
- image data
- input image
- object recognition
- machine learning
- image features
- tissue samples
- multiple images
- image retrieval
- unsupervised learning
- cell nuclei
- congestion control
- decision trees
- pattern recognition
- text classification
- supervised learning
- real world
- cancer diagnosis
- microscopy images
- restricted boltzmann machine
- feature vectors
- feature space