Nuclear segmentation based on endocytoscopy system with high magnification

Wei ZHANG; Hao YU; Bo YUAN; Li-qiang WANG; Qing YANG

doi:10.37188/OPE.2021.0324

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Nuclear segmentation based on endocytoscopy system with high magnification

Modern Applied Optics | 更新时间：2022-01-25

- Nuclear segmentation based on endocytoscopy system with high magnification
- Optics and Precision Engineering Vol. 29, Issue 11, Pages: 2574-2580(2021)
- 作者机构：
  
  1.浙江大学光电科学与工程学院，浙江杭州 310027
  2.之江实验室超级感知研究中心，浙江杭州 311100
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.2021.0324
  CLC： R735.1;TP391.4
- Received：20 May 2021，
  
  Revised：04 June 2021，
  
  Published：15 November 2021
- 稿件说明：
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张伟,余浩,袁波等.基于高倍率细胞内镜系统的细胞核分割[J].光学精密工程,2021,29(11):2574-2580.

ZHANG Wei,YU Hao,YUAN Bo,et al.Nuclear segmentation based on endocytoscopy system with high magnification[J].Optics and Precision Engineering,2021,29(11):2574-2580.
张伟,余浩,袁波等.基于高倍率细胞内镜系统的细胞核分割[J].光学精密工程,2021,29(11):2574-2580. DOI： 10.37188/OPE.2021.0324.

ZHANG Wei,YU Hao,YUAN Bo,et al.Nuclear segmentation based on endocytoscopy system with high magnification[J].Optics and Precision Engineering,2021,29(11):2574-2580. DOI： 10.37188/OPE.2021.0324.

摘要

临床上诊断消化道早期癌症主要依赖于电子内镜活检术，但是其诊断周期长。细胞内镜是一种具有超高放大倍率的内窥镜，配合术中染色可以直接在体内观察到病灶的细胞核等病理结构。为了使内窥镜医生能够在术中更准确地分析细胞核病理特征，基于已研制的高倍率细胞内镜系统在猪食管黏膜组织上开展了细胞核染色及分割方法研究。利用1%浓度的甲苯胺蓝水溶液对猪食管黏膜进行细胞核染色，并成功在细胞内镜显微成像模式下观察到染色的细胞核。在此基础上，采用深度学习方法训练了细胞核分割模型，有效实现了染色细胞核的分割提取，分割准确度达到了99.23%，特异性达到了99.54%，敏感性达到了84.37%，Dice系数达到了0.813 8，为细胞内镜的AI辅助诊断算法研究奠定了基础。

Abstract

Endoscopic biopsy is the main approach to the clinical diagnosis of early gastrointestinal cancer to date. However， this approach warrants a long period to obtain the final diagnosis. Endocytoscopy is a type of endoscope with ultra-high magnification， which， combined with intraoperative staining， can directly observe the pathological structure of the lesion such as the nucleus in vivo. To make endoscopists more accurately analyze the pathological features of the nucleus during the operation， a nuclear staining and segmentation method was previously developed for the esophageal mucosa tissue of pigs based on the endocytoscopy system with high magnification. Firstly， 1% toluidine blue was used to stain the nucleus of esophageal mucosa tissue， and the stained nuclei were observed successfully under the microscopic imaging mode of endocytoscopy. Based on this， the deep learning method was adopted to train the nuclear segmentation model， which effectively realized the segmentation and extraction of stained nuclei. The pixel accuracy reaches 99.23%， specificity of 99.54%， sensitivity of 84.37%， and the Dice of 0.813 8， laying a foundation for the study of artificial intelligence-assisted diagnosis of endocytoscopy.

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references

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