The aim of the study is to use the well-known channelized Hotelling observer model (CHO) to characterize a recently installed angiography system (GE Discovery IGS 740) using sets of images of a contrast-detail phantom acquired with clinical protocols. A Leeds TO10 phantom was used. The phantom has 108 details: 12 diameters (size range: 0.25 mm-11 mm), each with nine contrasts (declared range: 0.012-0.930 at 70 kVp 1.00 with 1 mm Cu filtration). TO10 has been imaged between two 10 cm thick homogeneous solid water slabs. Two FOVs (32 cm and 20 cm) were used. Fluoroscopy images were taken using an abdominal protocol at two different frame rates (15 fps and 7.5 fps) and at two dose levels (low and normal); cineangiography images were acquired using an abdominal protocol at 15 fps at two dose levels (low and normal). A 40 Gabor channels CHO with internal noise was used. Human observers' studies were carried out to tune the internal noise parameter and to validate the model observer. Contrast-detail curves were obtained from the CHO output using a visibility threshold of 75% and fitted with Rose's model theory in order to characterize the angiography system. Wilcoxon rank-sum tests were performed to investigate possible differences among the different sets of images. The CHO can distinguish between the two dose levels (p-values < 0.002), while FOV and frame rate do not affect the contrast-detail curves significantly. It is important to note that the CHO does not find statistically significant differences between a fluoroscopy with FOV = 20 cm at normal dose level (17.6 mGy min-1) and a cineangiography with FOV = 32 cm low dose level (42.1 mGy min-1). This result can lead to a dose reduction of about 70% for our specific task (i.e. a static, disc shaped object at known location in homogeneous field). Given their stability in comparison to human observers, model observers provide an effective tool for image quality evaluation.
- channelized Hotelling observer model
- image quality
- x-ray angiography
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging