No abstract

Introduction Deep learning image reconstruction (DLIR) is a very recent image reconstruction method that is already available for commercial use. We evaluated the quality of DLIR images and compared it to the quality of images from the latest adaptive statistical iterative reconstruction (ASIR-V) algorithm in terms of noise-power spectrum (NPS) and modulation-transfer function (MTF). Methods We scanned a Revolution QA phantom (GE Healthcare, USA) and a 20 cm water phantom (GE Healthcare, USA) with our 512 multi-slice computed tomography (CT) scanner. Images of the tungsten wire within the Revolution QA phantom were reconstructed with a 50 mm field of view (FOV). The images were reconstructed with various ASIR-V strengths (i.e. 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100%) and DLIRs (i.e. low, medium, and high) to assess the MTF. The images from the 20 cm water phantom were reconstructed with the same configuration to assess the NPS. Results The MTF was similar for both reconstruction algorithms of DLIR and ASiR-V. The peak frequency (fp) of the DLIR low was comparable to that from ASIR-V at 50, 60, 70%; the DLIR medium was comparable to ASIR-V at 80%; and the DLIR high was comparable to ASIR-V at 100%. The average frequency (fA) of the DLIR low was comparable to that from ASIR-V at 40%; the DLIR medium was comparable to ASIR-V at 50%; and the DLIR high was comparable to ASIR-V at 70%. Both the DLIR and ASIR-V were able to reduce noise, but they had a different texture. Conclusions The noise in the DLIR images was more homogenous at high and low frequencies, while in the ASIR-V images, the noise was more concentrated at high frequencies. The MTF was similar for both reconstruction algorithms. The DLIR method showed a better noise reduction than the ASIR-V reconstruction.

CT scan can be used to show the anatomical and pathological evaluation of Mastoid bones where an X-ray across it to create a cross-sectional image with an advanced computer. This imaging modality allows the radiologist to look at different levels of the bone ridge behind the ear. In our hospital, this procedure needs to be improved. Radiographer could make optimization by adjusting windows and developing kernel to maintain the image quality. This study aimed to obtain the optimum image of Mastoid bones, using variations of window and kernel reconstruction. The study was descriptive quantitative with an experimental approach. It resulted in eight images of two windowing levels (sinus and inner ear) and four kernel variations (smooth, medium, sharp, and ultra-sharp). Three radiologists evaluated the injury, bleedin, and soft tissue abnormalities images. The result showed that all window settings are acceptable. Kernel reconstructions have no different anatomical image information in soft tissue, Internal Auditory Canal, and External Auditory Canal. There is a difference for overall anatomical information of Mastoid bones (p value<0.05). Highest values of mean rank are obtained from sharp and ultra-sharp. Our recommendations are using the H.20s smooth kernel for soft tissue abnormalities and H.70s sharp kernel for fracture and bleeding cases.

Signal to Noise Ratio (SNR) is one of the quality control tests for most diagnostic imaging modality, including Magnetic Resonance Imaging (MRI). This study used MRI 1.5T GE Signa Creator type and head coil phantom with variations of Echo Time (TE), Repetition Time (TR), voxel volume and flip angle. 16 data images were obtained from the acquisition process. These images were analyzed using image processing software to calculate the SNR value. It results in four data distribution with the highest value of 36.98 and the lowest value of 32.64. The graphs of voxel volume versus SNR also formed four groups of data with an overall value above SNR baseline value for daily operation.

Verification of the irradiation set up is a process to ensure that the position and volume of the irradiated tumor are the same as planned. It is conducted by comparing the radiographic image information of the Treatment Planning System (TPS) with radiation therapy to be provided on the Electronic Portal Imaging Device (EPID). Existing software s on the EPID modality device in this hospital are Mosaiq and IViewGT. This study was to describe the details of the verification process and the differences between two software s in conformal radiotherapy of nasopharyngeal cancer patients. This study was a quantitative analytic study. Samples were fifty-two portal images. Data was analyzed by statistical software. The results are descriptions of the verification process, and the value of shift set up irradiation on X; Y and Z axis. There is no difference statistically between two software s. Mosaiq software is more complicated in image processing. IViewGT software has an advantage in its better simplicity but shows the same quality.