For all noise structures, detectability by a human observer is higher for multislice images than single-slice images, and the degree of detectability increase in multislice images depends on the noise structure. For model observer, channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels are used. Detectability is evaluated using human and model observer studies. To evaluate multislice images, central nine slices are used. To evaluate single-slice images, the central slice, which contains the maximum signal energy, is used. To generate different noise structures, two types of reconstruction filters (Hanning and Ram-Lak weighted ramp filters) are used in the reconstruction, and the transverse and longitudinal planes of reconstructed volume are used for detectability evaluation. CT projection data are acquired by the forward projection and reconstructed by the Feldkamp-Davis-Kress algorithm. Spherical signal with a 2 mm diameter is used for modeling a lesion. Anatomical background noise is modeled using a power law spectrum of breast anatomy. We investigate lesion detectability and its trends for different noise structures in single-slice and multislice CBCT images with anatomical background noise. multi- slice human and model observer study Lesion detection performance of cone beam CT images with anatomical background noise: single-slice vs. On the other hand, the quality of a CT image is more accurately estimated with clinical anatomical backgrounds. Our results suggest that for low contrast detection in abdominal CT, the use of multi- slice model observers would probably only add a marginal benefit. Regarding the background, performances are moderately higher for uniform than for anatomical images. Results show that observers don't take significantly benefit of additional information provided in multi- slice reading mode.
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We investigated detection performance and scrolling trends of human observers of a simulated liver lesion embedded in anatomical and uniform CT backgrounds. The purpose of this paper was to test if human observer performance is significantly different in CT images read in single or multiple slice modes and if these differences are the same for anatomical and uniform clinical images. Another limitation is that most of them only consider the detection of a signal embedded in a uniform background phantom. Human and mathematical model observers are increasingly used for the detection of low contrast signal in abdominal CT, but are frequently limited to the use of a single image slice. Image quality assessment is crucial for the optimization of computed tomography ( CT) protocols. Low contrast detection in abdominal CT: comparing single-slice and multi- slice tasksīa, Alexandre Racine, Damien Viry, Anaïs.