Paper
27 March 2008 The impact of pulmonary nodule size estimation accuracy on the measured performance of automated nodule detection systems
Sergei V. Fotin, Anthony P. Reeves, David F. Yankelevitz, Claudia I. Henschke
Author Affiliations +
Abstract
The performance of automated pulmonary nodule detection systems is typically qualified with respect to some minimum size of nodule to be detected. Also, an evaluation dataset is typically constructed by expert radiologists with all nodules larger than the minimum size being designated as true positives while all other smaller detected "nodules" are considered to be false positives. In this paper, we consider the negative impact that size estimation error, either in the establishment of ground truth for the evaluation dataset or by the automated detection method for the size estimate of nodule candidates, has on the measured performance of the detection system. Furthermore, we propose a modified evaluation procedure that addresses the size estimation error issue. The impact of the size measurement error was estimated for a documented research image database consisting of whole-lung CT scans for 509 cases in which 690 nodules have been documented. We compute FROC curves both with and without size error compensation and we found that for a minimum size limit of 4 mm the performance of the system is underestimated by a sensitivity reduction of 5% and a false positive rate increase of 0.25 per case. Therefore, error in nodule size estimation should be considered in the evaluation of automated detection systems.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergei V. Fotin, Anthony P. Reeves, David F. Yankelevitz, and Claudia I. Henschke "The impact of pulmonary nodule size estimation accuracy on the measured performance of automated nodule detection systems", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 69151G (27 March 2008); https://doi.org/10.1117/12.770695
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Error analysis

Computing systems

Databases

Detection and tracking algorithms

Computed tomography

Solids

Visibility

Back to Top