脑肿瘤图像分类识别探索综述与实验:人工智能技术的初步经验

Changhao Ding, Wenbo Zheng
{"title":"脑肿瘤图像分类识别探索综述与实验:人工智能技术的初步经验","authors":"Changhao Ding, Wenbo Zheng","doi":"10.1109/ICAICE54393.2021.00008","DOIUrl":null,"url":null,"abstract":"In this paper, we aim to focus on accurate brain tumor classification. We utilize two popular models, including AlexNet and VGG to realize the recognition of brain tumor dataset. We firstly pre-process and apply data enhancement for the given dataset and then, use those two model for classification. In conclusion, we found that the VGGNet is superior to AlexNet with a large margin and achieves a reasonable performance with 78.2%. Our paper provides a brief attempt for medical image classification.","PeriodicalId":388444,"journal":{"name":"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Summary and Experiment on the Exploration of Brain Tumor Image Classification Recognition: Initial Experience of Artificial Intelligence Technology\",\"authors\":\"Changhao Ding, Wenbo Zheng\",\"doi\":\"10.1109/ICAICE54393.2021.00008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we aim to focus on accurate brain tumor classification. We utilize two popular models, including AlexNet and VGG to realize the recognition of brain tumor dataset. We firstly pre-process and apply data enhancement for the given dataset and then, use those two model for classification. In conclusion, we found that the VGGNet is superior to AlexNet with a large margin and achieves a reasonable performance with 78.2%. Our paper provides a brief attempt for medical image classification.\",\"PeriodicalId\":388444,\"journal\":{\"name\":\"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAICE54393.2021.00008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICE54393.2021.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们的目标是集中在准确的脑肿瘤分类。我们利用AlexNet和VGG两种流行的模型来实现对脑肿瘤数据集的识别。我们首先对给定的数据集进行预处理和数据增强,然后使用这两种模型进行分类。综上所述,我们发现VGGNet以较大的优势优于AlexNet,达到了78.2%的合理性能。本文为医学图像分类提供了一个简单的尝试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Summary and Experiment on the Exploration of Brain Tumor Image Classification Recognition: Initial Experience of Artificial Intelligence Technology
In this paper, we aim to focus on accurate brain tumor classification. We utilize two popular models, including AlexNet and VGG to realize the recognition of brain tumor dataset. We firstly pre-process and apply data enhancement for the given dataset and then, use those two model for classification. In conclusion, we found that the VGGNet is superior to AlexNet with a large margin and achieves a reasonable performance with 78.2%. Our paper provides a brief attempt for medical image classification.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信