title: Automation-assisted cervical cancer screening in manual liquid-based cytology with hematoxylin and eosin staining.
abstract: Current automation-assisted technologies for screening cervical cancer mainly rely on automated liquid-based cytology slides with proprietary stain. This is not a cost-efficient approach to be utilized in developing countries. In this article, we propose the first automation-assisted system to screen cervical cancer in manual liquid-based cytology (MLBC) slides with hematoxylin and eosin (H&E) stain, which is inexpensive and more applicable in developing countries. This system consists of three main modules: image acquisition, cell segmentation, and cell classification. First, an autofocusing scheme is proposed to find the global maximum of the focus curve by iteratively comparing image qualities of specific locations. On the autofocused images, the multiway graph cut (GC) is performed globally on the a* channel enhanced image to obtain cytoplasm segmentation. The nuclei, especially abnormal nuclei, are robustly segmented by using GC adaptively and locally. Two concave-based approaches are integrated to split the touching nuclei. To classify the segmented cells, features are selected and preprocessed to improve the sensitivity, and contextual and cytoplasm information are introduced to improve the specificity. Experiments on 26 consecutive image stacks demonstrated that the dynamic autofocusing accuracy was 2.06 μm. On 21 cervical cell images with nonideal imaging condition and pathology, our segmentation method achieved a 93% accuracy for cytoplasm, and a 87.3% F-measure for nuclei, both outperformed state of the art works in terms of accuracy. Additional clinical trials showed that both the sensitivity (88.1%) and the specificity (100%) of our system are satisfyingly high. These results proved the feasibility of automation-assisted cervical cancer screening in MLBC slides with H&E stain, which is highly desirable in community health centers and small hospitals.
authors.affiliation: Department of Biomedical Engineering, Shenzhen University, Shenzhen, 518060, China; National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Shenzhen, 518060, China; Guangdong Key Laboratory of Biomedical Information Detection and Ultrasound Imaging, Shenzhen, 518060, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Zhang
authors.forename: Hui
authors.initials: H
authors.lastname: Kong
authors.forename: Chien
authors.initials: C
authors.lastname: Ting Chin
authors.forename: Shaoxiong
authors.initials: S
authors.lastname: Liu
authors.forename: Xinmin
authors.initials: X
authors.lastname: Fan
authors.forename: Tianfu
authors.initials: T
authors.lastname: Wang
authors.forename: Siping
authors.initials: S
authors.lastname: Chen
mesh_terms: D001331:Automation / Q000191:economics / Q000379:methods; D002467:Cell Nucleus / Q000473:pathology; D003362:Cost-Benefit Analysis; D003593:Cytoplasm / Q000378:metabolism; D055088:Early Detection of Cancer; D004801:Eosine Yellowish-(YS); D005260:Female; D006416:Hematoxylin; D006801:Humans; D012680:Sensitivity and Specificity; D013194:Staining and Labeling / Q000379:methods; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*
chemical_list: D004801:Eosine Yellowish-(YS); D006416:Hematoxylin
keywords: H&E stain; automation-assisted screening; cervical cancer; cervical cell classification; cervical cell segmentation; developing countries; manual liquid-based cytology