The Effectiveness of Data Augmentation for Mature White Blood Cell Image Classification in Deep Learning — Selection of an Optimal Technique for Hematological Morphology Recognition

• Published in: IEICE Transactions on Information and Systems Vol. E106.D; no. 5; pp. 707 - 714
• Main Authors: NOZAKA, Hiroyuki, KAMATA, Kosuke, YAMAGATA, Kazufumi
• Format: Journal Article
• Language: English
• Published: Tokyo The Institute of Electronics, Information and Communication Engineers 01.05.2023; Japan Science and Technology Agency
• Subjects: Accuracy; Artificial intelligence; Blood; convolutional neural network; Data augmentation; Deep learning; Distortion; Effectiveness; hematology; Image classification; Image contrast; Leukocytes; Machine learning; medical artificial intelligence; Medical imaging; Rotation; Training; white blood cell
• ISSN: 0916-8532; 1745-1361
• DOI: 10.1587/transinf.2022DLP0066

The data augmentation method is known as a helpful technique to generate a dataset with a large number of images from one with a small number of images for supervised training in deep learning. However, a low validity augmentation method for image recognition was reported in a recent study on artifi...