The blood cell counting and classification ensures the evaluation and diagnosis of a number of diseases. The analysis of white blood cells (WBCs) permits us to detect the acute lymphoblastic leukemia (ALL), a type of blood cancer that causes fatality when untreated. At present, the morphological analysis of blood cells is performed manually by skilled operators, which holds numerous drawbacks. The manual techniques for leukemia detection are time-consuming and show less accurate results. Hence, there is a need for an automatic method for detecting leukemia. In order to overcome the demerits associated with the manual methods of counting and classifying, an automatic method of blast cell counting and leukemia classification is progressed. This paper proposes a leukemia detection method, using the Gini index–based Fuzzy Naive Bayes (GFNB) classifier that is the integration of Gini index and Fuzzy Naive Bayes classifier. Initially, the input multi-cell blood smear image is subjected to pre-processing, and the blast cell is segmented using the adaptive thresholding. Then, the blast cells are counted using the proposed classifier so as to decide the presence of leukemia for the effective diagnosis. Experimental analysis using the ALL-IDB1 database confirms that the proposed method operates better than the existing methods in terms of accuracy, specificity, and sensitivity that are found to be 0.9591, 0.9599, and 1, respectively. The experimental results reveal that the proposed method is reliable and accurate. Also, the proposed system can help the physicians to improve and speed up their process.

Graphical abstract

血细胞计数和分类确保了许多疾病的评估和诊断。对白细胞 (WBC) 的分析使我们能够检测急性淋巴细胞白血病 (ALL)，这是一种在未经治疗时会导致死亡的血癌。目前，血细胞的形态学分析是由熟练的操作人员手动进行的，存在许多缺点。白血病检测的手动技术非常耗时，而且结果不太准确。因此，需要一种用于检测白血病的自动方法。为了克服手动计数和分类方法的缺点，提出了一种原始细胞计数和白血病分类的自动方法。本文提出了一种白血病检测方法，使用基于基尼指数的模糊朴素贝叶斯（GFNB）分类器，即基尼指数和模糊朴素贝叶斯分类器的集成。首先，对输入的多细胞血涂片图像进行预处理，并使用自适应阈值分割原始细胞。然后，使用建议的分类器对原始细胞进行计数，以确定是否存在白血病以进行有效诊断。使用 ALL-IDB1 数据库的实验分析证实，所提出的方法在准确性、特异性和灵敏度方面优于现有方法，分别为 0.9591、0.9599 和 1。实验结果表明，所提出的方法是可靠和准确的。此外，提议的系统可以帮助医生改进和加快他们的过程。

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