White blood cells segmentation and classification using U-Net CNN and hand-crafted features
Author:
Affiliation:
1. Univerity of Engineering and Technology,Department of Electrical Engineering,Taxila,Pakistan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9987718/9988932/09988955.pdf?arnumber=9988955
Reference21 articles.
1. A Cascaded Classification-Segmentation Reversible System for Computer-Aided Detection and Cells Counting in Microscopic Peripheral Blood Smear Basophils and Eosinophils Images
2. Red blood cell and white blood cell classification using double thresholding and BLOB analysis
3. White blood cells detection and classification based on regional convolutional neural networks
4. New segmentation and feature extraction algorithm for classification of white blood cells in peripheral smear images
5. Feature extraction using traditional image processing and convolutional neural network methods to classify white blood cells: a study
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1. AML leukocyte classification method for small samples based on ACGAN;Biomedical Engineering / Biomedizinische Technik;2024-03-29
2. Improving the accuracy of segmentation of white blood cells (WBCs) in microscopic images using watershed algorithm in comparison with adaptive thresholding;AIP Conference Proceedings;2024
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