本文提出了一种增强的分割方法，用于准确检测血涂片图像中的急性淋巴细胞白血病 (ALL)。所提出的方法将颜色校正技术与 HSV 颜色空间分割相结合，以改进白细胞分析。我们的方法解决了显微图像处理中的常见挑战，包括传感器非线性、照明不均匀和颜色失真。本研究的主要目标是开发一个强大的预处理流程，对血涂片图像进行标准化以进行一致分析，实施针对白细胞检测优化的基于 HSV 的分割技术，并使用临床样本验证该方法在各种 ALL 亚型中的有效性。使用所有患者的真实血涂片样本对所提出的技术进行了评估。定量分析表明，与传统方法相比，分割精度显着提高。我们的方法显示出可靠检测和分割所有亚型的强大能力，为临床环境中增强诊断支持提供了潜力。© 2024 Wiley periodicals LLC。

This article presents an enhanced segmentation methodology for the accurate detection of acute lymphoblastic leukemia (ALL) in blood smear images. The proposed approach integrates color correction techniques with HSV color space segmentation to improve white blood cell analysis. Our method addresses common challenges in microscopic image processing, including sensor nonlinearity, uneven illumination, and color distortions. The key objectives of this study are to develop a robust preprocessing pipeline that normalizes blood smear images for consistent analysis, implement an HSV-based segmentation technique optimized for leukocyte detection, and validate the method's effectiveness across various ALL subtypes using clinical samples. The proposed technique was evaluated using real-world blood smear samples from ALL patients. Quantitative analysis demonstrates significant improvements in segmentation accuracy compared to traditional methods. Our approach shows strong capability in reliably detecting and segmenting ALL subtypes, offering the potential for enhanced diagnostic support in clinical settings.© 2024 Wiley Periodicals LLC.