Classification of Cancer Microscopic Images via Convolutional Neural Networks

被引：6
|
作者：
Khan, Mohammad Azam [1 ]
Choo, Jaegul [1 ]
机构：
[1] Korea Univ, Seoul 136713, South Korea
来源：
ISBI 2019 C-NMC CHALLENGE: CLASSIFICATION IN CANCER CELL IMAGING | 2019年
关键词：
B-lymphoblast cell; Blood smear; B-lymphoid; Blood cancer; Convolutional neural networks;
D O I：
10.1007/978-981-15-0798-4_15
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes our approach for the classification of normal versus malignant cells in B-ALL white blood cancer microscopic images: ISBI 2019- classification of leukemic B-lymphoblast cells from normal B-lymphoid precursors from blood smear microscopic images. We leverage a state of the art convolutional neural network pretrained with the ImageNet dataset and applied several data augmentation and hyperparameters optimization strategies. Our method obtains an F1 score of 0.83 for the final test set in the competition.
引用
收藏
页码：141 / 147
页数：7
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