Investigation of Deep Learning Schemes in Medical Application

被引:0
|
作者
Velliangiri, S. [1 ]
Karthikeyan, P. [2 ]
Joseph, Iwin Thanakumar [3 ]
Kumar, Satish A. P. [4 ]
机构
[1] CMR Inst Technol, Hyderabad, India
[2] Presidency Univ, Dept CSE, Bangalore, Karnataka, India
[3] Karunya Inst Technol & Sci Coimbatore, CSE, Coimbatore, Tamil Nadu, India
[4] Coastal Carolina Univ, Dept Comp Sci, Conway, SC USA
来源
PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND KNOWLEDGE ECONOMY (ICCIKE' 2019) | 2019年
关键词
Deep Learning; Neural network; Conventional Neural Network; Medical application; SEGMENTATION; NETWORK;
D O I
10.1109/iccike47802.2019.9004238
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Deep learning models are equipped for thinking out how to concentrate on the correct features without anyone else's input, requiring a little direction from the software engineer. Essentially, deep learning mirrors how our brain is functioning to take decisions. Deep learning techniques are highly applied in medical imaging diagnosis. Deep learning techniques are used in medical applications in four different areas i. Detections ii. Classifications iii. Segmentations iv. Registrations. In this paper we have discussed deep learn scheme advantage, dataset, software and hardware used in medical applications. Further, we discussed the comparative analysis of medical application using deep learning techniques.
引用
收藏
页码:87 / 92
页数:6
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