A Neural-Network-Based Approach to White Blood Cell Classification
This paper presents a new white blood cell classification system for the recognition of five types of white blood cells. We propose a new segmentation algorithm for the segmentation of white blood cells from smear images. The core idea of the proposed segmentation algorithm is to find a discriminati...
Saved in:
| Main Authors: | Mu-Chun Su, Chun-Yen Cheng, Pa-Chun Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/796371 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automatic Classification of White Blood Cells Using a Semi-Supervised Convolutional Neural Network
by: Huihui Song, et al.
Published: (2024-01-01) -
An explainable AI-based blood cell classification using optimized convolutional neural network
by: Oahidul Islam, et al.
Published: (2024-12-01) -
Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization
by: Taeyeon Gil, et al.
Published: (2025-01-01) -
Multi-View Graph Contrastive Neural Networks for Session-Based Recommendation
by: Pengbo Huang, et al.
Published: (2025-05-01) -
A deep learning approach for white blood cells image generation and classification using SRGAN and VGG19
by: Jannatul Ferdousi, et al.
Published: (2024-12-01)