Artificial images for classifying diffuse lung opacities in thin-section computed tomography images

被引：0
|
作者：
Mitani, Y [1 ]
Matsunaga, N [1 ]
Hamamoto, Y [1 ]
机构：
[1] Ube Natl Coll Technol, Ube, Yamaguchi 7558555, Japan
来源：
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3 | 2004年
关键词：
D O I：
10.1109/ICPR.2004.1334583
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The classification of diffuse lung opacities in thin-section computed tomography(HRCT) images is very fundamental for developing a computer-aided diagnosis(CAD) system. However, in designing such a CAD system, the number of the available samples is usually small. This leads to the difficulties of designing the CAD system. One way to overcome this problem is to generate artificial images from available real images by image rotation and reversal. In this paper,we discuss the use of artificial images for designing the CAD system.
引用
收藏
页码：530 / 533
页数：4
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