Ensemble Convolutional Neural Networks for Cell Classification in Microscopic Images

被引：11

作者：

Shi, Tian ^{[1
]}

Wu, Longshi ^{[1
]}

Zhong, Changhong ^{[1
]}

Wang, Ruixuan ^{[1
]}

Zheng, Weishi ^{[1
]}

机构：

[1] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou, Peoples R China

来源：

ISBI 2019 C-NMC CHALLENGE: CLASSIFICATION IN CANCER CELL IMAGING | 2019年

关键词：

Convolutional neural networks; Ensemble model; Cell classification;

D O I：

10.1007/978-981-15-0798-4_5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this challenge, we address the cell classification problem using deep convolutional neural networks (CNNs). For a better generalization of the CNN classifier, various data augmentation and preprocessing were tested and an ensemble of state-of-the-art CNNs was adopted. In addition, to check the stability of the CNN model, the Grad-CAM technique was used to visualize the most discriminative part of each cell when predicting the category of the cell image. Our model achieves an accuracy of 86.9% in the preliminary testing and 87.9% in the final testing.

引用

页码：43 / 51

页数：9

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