stands for Digital Object Identifier
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.
Using DOI as a persistent link
To create a persistent link, add「http://dx.doi.org/」
before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.
Cite a document with DOI
When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.
DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ） 。
-  J. R. Muhm, W. E. Miller, R. S. Fontana, D. R. Sanderson, and M. A. Uhlenhopp, “Lung cancer detected during a screening program using four-month chest radiographs,” Radiology, vol. 148, no. 3, pp. 609-615, 1983.
-  J. Shiraishi, S. Katsuragawa, J. Ikezoe, T. Matsumoto, T. Kobayashi, K. I. Komatsu, M. Matsui, H. Fujita, Y. Kodera, and K. Doi, “Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules,” American journal of roentgenology, vol. 174, no. 1, pp. 71-74, 2000.
-  A. M. R. Schilham, B. V. Ginneken, and M. Loog, “A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database,” Medical Image Analysis, vol. 10, no. 2, pp. 247-258, 2006.
-  Z. Y. Chen, B. R. Abidi, D. L. Page, and M. A. Abidi, “Gray-level grouping (GLG): an automatic method for optimized image contrast Enhancement-part I: the basic method,” IEEE Trans. Image Process., vol. 15, no. 8, pp. 2290-2302, 2006.
-  J. Cabello, A. Bailey, I. Kitchen, M. Guy, and K. Wells, “Segmentation of low contrast-to-noise ratio images applied to functional imaging using adaptive region growing,” in Proc, Proceedings of SPIE, 2009, pp. 725940-725940-12.
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