Discrete-space versus continuous-space lesion boundary and area definitions.
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.
Department of Radiology, The University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637, USA. wfsensak@uchicago.edu
William F
WF
Sensakovic
Adam
A
Starkey
Rachael Y
RY
Roberts
Samuel G
SG
Armato
D000465:Algorithms; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted