scholarly journals A NEW CONCEPT OF DISCRETIZATION MODEL FOR IMAGING IMPROVING IN ULTRASOUND TRANSMISSION TOMOGRAPHY

Author(s):  
Tomasz Rymarczyk ◽  
Krzysztof Polakowski ◽  
Jan Sikora

In this paper a new version of discretization model for Ultrasonic Transmission Tomography is presented. The algorithm has been extensively tested for synthetic noisy data on various configurations of internal objects. In order to improve the imaging quality, the pixels/voxels have been enlarged compared to the figures inscribed in pixels/voxels however no more than figures described on the standard square pixels or cubic voxels. The proposed algorithm provides better quality of imaging.

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan

Knowledge discovery is the process of adding knowledge from a large amount of data. The quality of knowledge generated from the process of knowledge discovery greatly affects the results of the decisions obtained. Existing data must be qualified and tested to ensure knowledge discovery processes can produce knowledge or information that is useful and feasible. It deals with strategic decision-making for an organization. Combining multiple operational databases and external data create the data warehouse. This treatment is very vulnerable to incomplete, inconsistent, and noisy data. Data mining provides a mechanism to clear this deficiency before finally stored in the data warehouse. This research tries to give technique to improve the quality of information in the data warehouse.


Optik ◽  
2018 ◽  
Vol 157 ◽  
pp. 298-305
Author(s):  
Liang Guo ◽  
Wei Li ◽  
Xiaozhen Li ◽  
Guanglie Hong ◽  
Jiangfeng Zhu ◽  
...  

2009 ◽  
Vol 29 (10) ◽  
pp. 2774-2779
Author(s):  
刘丽 Liu Li ◽  
江月松 Jiang Yuesong ◽  
王长伟 Wang Changwei

2015 ◽  
Vol 35 (4) ◽  
pp. 0416004
Author(s):  
刘逢芳 Liu Fengfang ◽  
朱兆杰 Zhu Zhaojie ◽  
童元伟 Tong Yuanwei

2010 ◽  
Vol 20 (1) ◽  
pp. 71-75 ◽  
Author(s):  
José M. Artigas ◽  
Adelina Felipe ◽  
Manuel Díaz-Llopis ◽  
Salvador García-Delpech ◽  
Amparo Navea

2020 ◽  
Vol 59 (01) ◽  
pp. 1
Author(s):  
Xinhai Zhao ◽  
Shihe Yi ◽  
Haolin Ding

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