Aceso: A Medical Image Analysis Platform Using Deep Learning

被引:0
|
作者
Nguyen, Tan H. [1 ]
Pham Duy Hai [2 ]
Cong Son Doan Huynh [3 ]
Huy Tan Nguyen [4 ]
机构
[1] NVIDIA Deep Learning Inst, IT Dept, Ho Chi Minh City, Vietnam
[2] FPT Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam
[3] HCMUTE, Fac Elect Engn Technol, Ho Chi Minh City, Vietnam
[4] Van Lang Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam
来源
2021 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR) | 2021年
关键词
Radiology; Aceso Platform; Deep Learning; !text type='Python']Python[!/text; Medical Image Analysis; Machine Learning;
D O I
10.1109/AIPR52630.2021.9762190
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Universally, deep learning researchers and medical professionals have always had a gap that hinders their interaction: their expertise or use of technology. To bridge this gap, we have developed a medical image analysis platform that uses deep learning to make it easier for them to work together. We have built the third version platform where users can upload and process a medical image to check, research, aid in their diagnosis or training. Unfortunately, open-source codes are unavailable, but we allow users to download the free trial version on their local server. This article will discuss the three main contents in detail: how we have built the platform, how it supports users, and how we use models in our system. Primarily, we have integrated some popular models into this platform with a dataset of over 180,000 patients. In addition, the platform can help us detect 20 different diseases related to the lungs, such as Covid-19, Pneumonia, Atelectasis, Consolidation, Edema, Effusion, Lung Lesion, etc. The models' Accuracy is over 90 percent. The platform is freely available on the website: https://aceso.tech/ (*). Note: we have split our platform into 14 classes, 18 classes, and 20 classes.
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页数:6
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