MO‐D‐332‐03: Scatter Rejection Properties and Low‐Contrast Performance of a Scan Equalization Digital Radiography (SEDR) System: Initial Experience with Chest Phantom Images

Purpose: To investigate scatter rejection properties and low‐contrast performance of a flat‐panel based SEDR system for chest imaging. Method and Materials: A prototype SEDR system was developed to improve the image quality especially in heavily attenuated regions. Slot scan imaging geometry was used to reduce x‐ray scatter without attenuating primary x‐rays. Regional beam width modulation was used to equalize the x‐ray exposures at the detector input for more uniform image signal‐to‐noise ratios. A low‐dose chest phantom (pre‐scan) image was acquired with the slot‐scan technique to determine the equalization factors for SEDR imaging. A steel bar was placed in front of the chest phantom to measure the scatter component and scatter‐to‐primary ratios (SPRs) across the phantom image. Two images acquired with the same techniques were subtracted from each other for measuring the noise levels. SPRs, SNRs, and contrast‐to‐noise ratios (CNRs) of the SEDR images were measured and compared with those of the slot‐scan images and full‐field images acquired with and without anti‐scatter grid. Results: The SEDR technique resulted in lower SPRs in heavily attenuated regions like retrocardum and mediastinum than the slot‐scan and full‐field techniques. They resulted in similar SPRs in lungs as the slot‐scan technique. Both the SEDR and slot‐scan methods produced better SNRs than the anti‐scatter grid method in full‐field imaging. The SEDR technique resulted in the best CNRs, followed in order by the slot‐scan and anti‐scatter grid techniques. The improvement of CNR was more pronounced in heavily attenuated regions. Conclusion: The SEDR technique can effectively reject scatter without having to attenuate the primary x‐rays. Furthermore, it can improve image SNRs and CNRs by regionally compensating for x‐ray attenuation by patient's anatomy. Acknowledgement: This work was supported in part by grants CA104759 and CA124585 from NIH‐NCI, a grant EB00117 from NIH‐NIBIB, and a subcontract from NIST‐ATP.