Discrete-space versus continuous-space lesion boundary and area definitions.

Saved in:

Bibliographic Details
Title:	Discrete-space versus continuous-space lesion boundary and area definitions.
Authors:	Sensakovic, William F.¹ wfsensak@uchicago.edu, Starkey, Adam¹, Roberts, Rachael Y.¹, Armato III, Samuel G.¹
Source:	Medical Physics. Sep2008, Vol. 35 Issue 9, p4070-4078. 9p. 1 Black and White Photograph, 2 Diagrams, 2 Charts, 4 Graphs.
Subjects:	Medical imaging systems, Image processing, Lung disease diagnosis, Precancerous conditions, Databases, Medical physics, Education
Abstract:	Measurement of the size of anatomic regions of interest in medical images is used to diagnose disease, track growth, and evaluate response to therapy. The discrete nature of medical images allows for both continuous and discrete definitions of region boundary. These definitions may, in turn, support several methods of area calculation that give substantially different quantitative values. This study investigated several boundary definitions (e.g., continuous polygon, internal discrete, and external discrete) and area calculation methods (pixel counting and Green’s theorem). These methods were applied to three separate databases: A synthetic image database, the Lung Image Database Consortium database of lung nodules and a database of adrenal gland outlines. Average percent differences in area on the order of 20% were found among the different methods applied to the clinical databases. These results support the idea that inconsistent application of region boundary definition and area calculation may substantially impact measurement accuracy. [ABSTRACT FROM AUTHOR]
	Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Engineering Source

Description
Abstract:	Measurement of the size of anatomic regions of interest in medical images is used to diagnose disease, track growth, and evaluate response to therapy. The discrete nature of medical images allows for both continuous and discrete definitions of region boundary. These definitions may, in turn, support several methods of area calculation that give substantially different quantitative values. This study investigated several boundary definitions (e.g., continuous polygon, internal discrete, and external discrete) and area calculation methods (pixel counting and Green’s theorem). These methods were applied to three separate databases: A synthetic image database, the Lung Image Database Consortium database of lung nodules and a database of adrenal gland outlines. Average percent differences in area on the order of 20% were found among the different methods applied to the clinical databases. These results support the idea that inconsistent application of region boundary definition and area calculation may substantially impact measurement accuracy. [ABSTRACT FROM AUTHOR]
ISSN:	00942405
DOI:	10.1118/1.2963989