Correlation between human observer performance and model observer performance in differential phase contrast CT. Issue 11 (10th October 2013)

• Record Type: Journal Article
• Authors: Li, Ke; Garrett, John; Chen, Guang‐Hong
• Is Part Of: Medical physics. Volume 40:Issue 11(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-10-10
• Subjects: Computed tomography -- X‐ray imaging -- Stochastic modeling; computerised tomography -- medical image processing -- stochastic processes; differential phase contrast CT -- detectability index -- model observer -- human observer -- alternative forced choice; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Medical imaging -- Medical image noise -- Experiment design -- Medical X‐ray imaging -- Computed tomography -- Medical image contrast -- Image reconstruction -- Medical image reconstruction -- Image detection systems -- X‐ray imaging; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4822576
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : With the recently expanding interest and developments in x‐ray differential phase contrast CT (DPC‐CT), the evaluation of its task‐specific detection performance and comparison with the corresponding absorption CT under a given radiation dose constraint become increasingly important. Mathematical model observers are often used to quantify the performance of imaging systems, but their correlations with actual human observers need to be confirmed for each new imaging method. This work is an investigation of the effects of stochastic DPC‐CT noise on the correlation of detection performance between model and human observers with signal‐known‐exactly (SKE) detection tasks. Methods: : The detectabilities of different objects (five disks with different diameters and two breast lesion masses) embedded in an experimental DPC‐CT noise background were assessed using both model and human observers. The detectability of the disk and lesion signals was then measured using five types of model observers including the prewhitening ideal observer, the nonprewhitening (NPW) observer, the nonprewhitening observer with eye filter and internal noise (NPWEi), the prewhitening observer with eye filter and internal noise (PWEi), and the channelized Hotelling observer (CHO). The same objects were also evaluated by four human observers using the two‐alternative forced choice method. The results from the model observer experiment were quantitatively compared to the human observer results to assess the correlation between the two techniques. Results: : The contrast‐to‐detail (CD) curve generated by the human observers for the disk‐detection experiments shows that the required contrast to detect a disk is inversely proportional to the square root of the disk size. Based on the CD curves, the ideal and NPW observers tend to systematically overestimate the performance of the human observers. The NPWEi and PWEi observers did not predict human performance well either, as the slopes of their CD curves tended to be steeper. The CHO generated the best quantitative agreement with human observers with its CD curve overlapping with that of human observer. Statistical equivalence between CHO and humans can be claimed within 11% of the human observer results, including both the disk and lesion detection experiments. Conclusions: : The model observer method can be used to accurately represent human observer performance with the stochastic DPC‐CT noise for SKE tasks with sizes ranging from 8 to 128 pixels. The incorporation of the anatomical noise remains to be studied.