Cao Guitao, Li Ling, Chen Weiting, Yu Yehua, Shi Jun, Zhang Guixu, Liu Xuehua
Software Engineering Institute, East China Normal University, 3663 North Zhongshan Road, Shanghai, 200062, China,
Med Biol Eng Comput. 2015 Mar;53(3):215-26. doi: 10.1007/s11517-014-1223-1. Epub 2014 Nov 28.
Abnormal localization of immature precursors (ALIP) aggregating and clustering in bone marrow biopsy appears earlier than that of bone marrow smears in detection of the relapse of acute myelocytic leukemia (AML). But traditional manual ALIP recognition has many shortcomings such as prone to false alarms, neglect of distribution law before three immature precursor cells gathered, and qualitative analysis instead of quantitative one. So, it is very important to develop a novel automatic method to identify and localize immature precursor cells for computer-aided diagnosis, to disclose their patterns before ALIP with the development of AML. The contributions of this paper are as follows. (1) After preprocessing the image with Otsu method, we identify both precursor cells and trabecular bone by multiple morphological operations and thresholds. (2) We localize the precursors in different regions according to their distances with the nearest trabecular bone based on chamfer distance transform, followed by discussion for the presumptions and limitations of our method. The accuracy of recognition and localization is evaluated based on a comparison with visual evaluation by two blinded observers.
在急性髓细胞白血病(AML)复发检测中,骨髓活检中未成熟前体细胞异常定位(ALIP)的聚集和簇集现象比骨髓涂片出现得更早。但传统的手动ALIP识别存在诸多缺点,如容易误报、忽视三个未成熟前体细胞聚集前的分布规律,以及定性分析而非定量分析等。因此,开发一种新颖的自动方法来识别和定位未成熟前体细胞以用于计算机辅助诊断,揭示AML发展过程中ALIP之前的细胞模式非常重要。本文的贡献如下:(1)用大津法对图像进行预处理后,通过多种形态学操作和阈值识别前体细胞和小梁骨。(2)基于倒角距离变换,根据前体细胞与最近小梁骨的距离在不同区域定位前体细胞,随后讨论了该方法的假设和局限性。基于与两位盲法观察者的视觉评估结果进行比较,评估识别和定位的准确性。