WBC-Profiler: an Unsupervised Feature Learning System for Leukocytes Characterization and Classification
The characterization and classification of white blood cells (WBC) is critical for the diagnosis of anemia, leukemia and many other hematologic diseases. We developed WBC-Profiler, an unsupervised feature learning system for quantitative analysis of leukocytes. We demonstrate that WBC-Profiler enables automatic extraction of complex signatures from microscopic images without human-intervention and thereafter effective construction of leukocytes profiles, which decouples large scale complex leukocytes characterization from limitations in both human-based feature engineering/optimization and the end-to-end solutions provided by modern deep neural networks, and therefore has the potential to provide new opportunities towards meaningful studies/applications with scientific and/or clinical impact
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