Details

Autor(en) / Beteiligte

• Khan, Siraj
• Sajjad, Muhammad
• Abbas, Naveed
• Escorcia-Gutierrez, José
• Gamarra, Margarita
• Muhammad, Khan

Titel

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network

Ist Teil von

• Computers in biology and medicine, 2024-05, Vol.174, p.108146-108146, Article 108146

Ort / Verlag

United States: Elsevier Ltd

Erscheinungsjahr

2024

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification in blood smears offers insights to pathologists, aiding diagnosis across medical conditions. Traditional techniques, including manual counting, detection, classification, and visual inspection of microscopic images by medical professionals, pose challenges due to their labor-intensive nature. However, traditional methods are time consuming and sometimes susceptible to errors. Here, we propose a high-performance convolutional neural network (CNN) coupled with a dual-attention network that efficiently detects and classifies WBCs in microscopic thick smear images. The main aim of this study was to enhance clinical hematology systems and expedite medical diagnostic processes. In the proposed technique, we utilized a deep convolutional generative adversarial network (DCGAN) to overcome the limitations imposed by limited training data and employed a dual attention mechanism to improve accuracy, efficiency, and generalization. The proposed technique achieved overall accuracy rates of 99.83%, 99.35%, and 99.60% for the peripheral blood cell (PBC), leukocyte images for segmentation and classification (LISC), and Raabin-WBC benchmark datasets, respectively. Our proposed approach outperforms state-of-the-art methods in terms of accuracy, highlighting the effectiveness of the strategies employed and their potential to enhance diagnostic capabilities and advance real-world healthcare practices and diagnostic systems. •An innovative method for generation of synthetic samples to enhance system's performance on leukocytes analysis tasks.•Dilated attention coupled CNN to enhance the diagnostics process for medical experts in diagnosing various hematic diseases.•A method to address the challenge of detecting and localizing different leukocytes’ sub-classes in blood smear images.