|Table of Contents|

Automatic Classification of Meningioma Subtype ImageBased on Convolutional Neural Network(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2018年03期
Page:
22-
Research Field:
·人工智能算法与应用专栏·
Publishing date:

Info

Title:
Automatic Classification of Meningioma Subtype ImageBased on Convolutional Neural Network
Author(s):
Fang Qianhao; Zhu Hong; He Hanzhi; Hu Junfeng
School of Medical Information,Xuzhou Medical University,Xuzhou 221004,China
Keywords:
meningioma; convolutional neural network; LeNet-5; meningioma subtype image classification
PACS:
TP181
DOI:
10.3969/j.issn.1001-4616.2018.03.004
Abstract:
Meningioma is the second most common tumor in the brain. The preoperative grading of meningioma can help develop clinical treatment plans and evaluate prognosis. In this paper,the LeNet-5 model of the convolutional neural network is improved from several aspects which include softmax layer,network structure,iterative rate of decline,and epoch for automatic classification of subtype images of meningioma. The model does not require the extraction of diseased tissue,which greatly improves the efficiency of automatic classification of meningioma images. Experiments show that the improved convolutional neural network model has a good effect on the classification of meningioma subtype images,and the highest correct rate reaches 91.18%.

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Last Update: 2018-11-19