• The Korean Journal of Nuclear Medicine Technology
• /
• v.13 no.1
• /
• pp.9-14
• /
• 2009

Purpose: Nowadays in the nuclear medicine, many studies and efforts are being made to reduce the scan time, as well as the waiting time to be needed to execute exams after injection of radionuclide medicines. Several methods are being used in clinic, such as developing new radionuclide compounds that enable to be absorbed into target organs more quickly and reducing acquisition scan time by increase the number of Gamma Camera detectors to examine. Each medical equipment manufacturer has improved the imaging process techniques to reduce scan time. In this paper, we tried to analyze the difference of image quality between FBP, 3D OSEM reconstruction methods that commercialized and being clinically applied, and Astonish reconstruction method (A kind of Iterative fast reconstruction method of Philips), also difference of image quality on scan time. Material and Methods: We investigated in 32 patients that examined the Bone SPECT from June to July 2008 at department of nuclear medicine, ASAN Medical Center in Seoul. 40sec/frame and 20sec/frame images were acquired that using Philips‘ PRECEDENCE 16 Gamma Camera and then reconstructed those images by using the Astonish (Philips’ Reconstruction Method), 3D OSEM and FBP methods. The blinded test was performed to the clinical interpreting physicians with all images analyzed by each reconstruction method for qualitative analysis. And we analyzed target to non target ratio by draws lesions as the center of disease for quantitative analysis. At this time, each image was analyzed with same location and size of ROI. Results: In a qualitative analysis, there was no significant difference by acquisition time changes in image quality. In a quantitative analysis, the images reconstructed Astonish method showed good quality due to better sharpness and distinguish sharply between lesions and peripheral lesions. After measuring each mean value and standard deviation value of target to non target ratio with 40 sec/frame and 20sec/frame images, those values are Astonish (40 sec-$13.91{\pm}5.62$ : 20 sec-$13.88{\pm}5.92$), 3D OSEM (40 sec-$10.60{\pm}3.55$ : 20 sec-$10.55{\pm}3.64$), FBP (40 sec-$8.30{\pm}4.44$ : 20 sec-$8.19{\pm}4.20$). We analyzed target to non target ratio from 20 sec and 40 sec images. And we analyzed the result, In Astonish (t=0.16, p=0.872), 3D OSEM (t=0.51, p=0.610), FBP (t=0.73, p=0.469) methods, there was no significant difference statistically by acquisition time change in image quality. But FBP indicates no statistical differences while some images indicate difference between 40 sec/frame and 20 sec/frame images by various factors. Conclusions: In the circumstance, try to find a solution to reduce nuclear medicine scan time, the development of nuclear medicine equipment hardware has decreased while software has marched forward at a relentless. Due to development of computer hardware, the image reconstruction time was reduced and the expanded capacity to restore enables iterative methods that couldn't be performed before due to technical limits. As imaging process technique developed, it reduced scan time and we could observe that image quality keep similar level. While keeping exam quality and reducing scan time can induce the reduction of patient's pain and sensory waiting time, also accessibility of nuclear medicine exam will be improved and it provide better service to patients and clinical physician who order exams. Consequently, those things make the image of department of nuclear medicine be improved. Concurrent Imaging - A new function that setting up each image acquisition parameter and enables to acquire images simultaneously with various parameters to once examine.

• Progress in Medical Physics
• /
• v.32 no.4
• /
• pp.92-98
• /
• 2021

Purpose: This study automatically discriminates homogeneous and structure edge regions on computed tomography (CT) images, and it evaluates the noise level and edge preservation ratio (EPR) according to the different types of iterative reconstruction (IR). Methods: The dataset consisted of CT scans of 10 patients reconstructed with filtered back projection (FBP), statistical IR (iDose⁴), and iterative model-based reconstruction (IMR). Using the 10th and 85th percentiles of the structure coherence feature, homogeneous and structure edge regions were localized. The noise level was estimated using the averages of the standard deviations for five regions of interests (ROIs), and the EPR was calculated as the ratio of standard deviations between homogeneous and structural edge regions on subtraction CT between the FBP and IR. Results: The noise levels were 20.86±1.77 Hounsfield unit (HU), 13.50±1.14 HU, and 7.70±0.46 HU for FBP, iDose⁴, and IMR, respectively, which indicates that iDose⁴ and IMR could achieve noise reductions of approximately 35.17% and 62.97%, respectively. The EPR had values of 1.14±0.48 and 1.22±0.51 for iDose⁴ and IMR, respectively. Conclusions: The iDose⁴ and IMR algorithms can effectively reduce noise levels while maintaining the anatomical structure. This study suggested automated evaluation measurements of noise levels and EPRs, which are important aspects in CT image quality with patients' cases of FBP, iDose⁴, and IMR. We expect that the inclusion of other important image quality indices with a greater number of patients' cases will enable the establishment of integrated platforms for monitoring both CT image quality and radiation dose.

• Journal of Korea Multimedia Society
• /
• v.20 no.6
• /
• pp.865-872
• /
• 2017

Recent advance in electronics and scintillators makes it possible to utilize the time-of-flight (TOF) information in improving image reconstruction of positron emission tomography(PET). In this paper, we propose a TOF-based fast image reconstruction method for PET. The proposed method uses the deconvolution of TOF data for each angle view and the rotational averaging of deconvolved images. Simulation results show an improved performance of the proposed method, as compared with filtered backprojection (FBP) method, TOF-FBP, and TOF version of expectation-maximization(EM) methods. Simulation results also show a great potentiality of the proposed method in limited angle tomography applications.

• Journal of radiological science and technology
• /
• v.40 no.2
• /
• pp.261-267
• /
• 2017

The study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying filter back projection (FBP), the existing test method, and adaptive statistical iterative reconstruction (ASIR) with different values of tube voltage during the low dose computed tomography (LDCT). With the image reconstruction method as basis, chest phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of tube voltage (100 kVp, 120 kVp). For image evaluation, back ground noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were measured, and, for dose assessment, CTDIvol and DLP were measured respectively. In terms of image evaluation, there was significant difference in ascending aorta (AA) SNR and inpraspinatus muscle (IM) SNR with the different amount of tube voltage (p < 0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120 kVp were 2.6 mGy with no-ASIR and 2.17 mGy with 20%-ASIR respectively, decreased by 0.43 mGy, and the values with 100 kVp were 1.61 mGy with no-ASIR and 1.34 mGy with 20%-ASIR, decreased by 0.27 mGy. In terms of DLP, the measured values with 120 kVp were $103.21mGy{\cdot}cm$ with no-ASIR and $85.94mGy{\cdot}cm$ with 20%-ASIR, decreased by $17.27mGy{\cdot}cm$ (about 16.7%), and the values with 100 kVp were $63.84mGy{\cdot}cm$ with no-ASIR and $53.25mGy{\cdot}cm$ with 20%-ASIR, a decrease by $10.62mGy{\cdot}cm$ (about 16.7%). At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.18 no.1
• /
• pp.69-75
• /
• 2014

Purpose: The aim of this study was to evaluate changes of quantitative and semi-quantitative myocardial perfusion indices and image quality by image reconstruction methods in $^{13}N$-ammonia ($^{13}N-NH_3$) myocardial perfusion PET/CT. Materials and Methods: Data of 14 (8 men, 6 women) patients underwent rest and adenosine stress $^{13}N-NH_3$ PET/CT (Biograph TruePoint 40 with TrueV, Siemens) were collected. Listmode scans were acquired for 10 minutes by injecting 370MBq of $^{13}N-NH_3$. Dynamic and static reconstruction was performed by use of FBP, iterative2D (2D), iterative3D (3D) and iterative TrueX (TrueX) algorithm. Coronary flow reserve (CFR) of dynamic reconstruction data, extent(%) and total perfusion deficit (TPD) (%) measured in sum of 4-10 minutes scan were evaluated by comparing with 2D method which was recommended by vendor. The image quality of each reconstructed data was compared and evaluated by five nuclear medicine physicians through a blind test. Results: CFR were lower in TrueX 18.68% (P=0.0002), FBP 4.35% (P=0.1243) and higher in 3D 7.91% (P<0.0001). As semi-quantitative values, extent and TPD of stress were higher in 3D 3.07%p (P=0.001), 2.36%p (P=0.0002), FBP 1.93%p (P=0.4275), 1.57%p (P=0.4595), TrueX 5.43%p (P=0.0003), 3.93%p (P<0.0001). Extent and TPD of rest were lower in FBP 0.86%p (P=0.1953), 0.57%p (P=0.2053) and higher in 3D 3.21%p (P=0.0006), 2.57%p (P=0.0001) and TrueX 5.36%p (P<0.0001), 4.36%p (P<0.0001). Based on the results of the blind test for image resolution and noise from the snapshot, 3D obtained the highest score, followed by 2D, TrueX and FBP. Conclusion: We found that quantitative and semi-quantitative myocardial perfusion values could be under- or over-estimated according to the reconstruction algorithm in $^{13}N-NH_3$ PET/CT. Therefore, proper dynamic and static reconstruction method should be established to provide accurate myocardial perfusion value.

• Nuclear Engineering and Technology
• /
• v.53 no.3
• /
• pp.888-893
• /
• 2021

The International Atomic Energy Agency has developed a tomographic imaging system for accomplishing the total fuel rod-by-rod verification time of fuel assemblies within the order of 1-2 h, however, there are still limitations for some fuel types. The aim of this study is to develop a deep learning-based denoising process resulting in increasing the tomographic image acquisition speed of fuel assembly compared to the conventional techniques. Convolutional AutoEncoder (CAE) was employed for denoising the low-quality images reconstructed by filtered back-projection (FBP) algorithm. The image data set was constructed by the Monte Carlo method with the FBP and ground truth (GT) images for 511 patterns of missing fuel rods. The de-noising performance of the CAE model was evaluated by comparing the pixel-by-pixel subtracted images between the GT and FBP images and the GT and CAE images; the average differences of the pixel values for the sample image 1, 2, and 3 were 7.7%, 28.0% and 44.7% for the FBP images, and 0.5%, 1.4% and 1.9% for the predicted image, respectively. Even for the FBP images not discriminable the source patterns, the CAE model could successfully estimate the patterns similarly with the GT image.

• Journal of the Korean Society of Radiology
• /
• v.17 no.3
• /
• pp.297-303
• /
• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• Journal of the Korean Society of Radiology
• /
• v.13 no.2
• /
• pp.159-168
• /
• 2019

We examined the effect of Siemens ADMIRE (Advanced Modeled Iterative Reconstruction) on image quality by measuring changes in HU, noise, and SNR of background air, fat, muscle, and background signals on a chest CT scan. Experimental results show that as the ADMIRE Strength increases, the noise decreases and the signal increases, consequently the signal-to-noise ratio increases. ADMIRE can reduce noise by 28 ~ 61% compared to FBP, which is a conventional image reconstruction algorithm, and improves SNR by 16 ~ 100%.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.7
• /
• pp.1001-1007
• /
• 2014

This paper proposes a method to reduce operation time using discrete cosine transform and to improve image quality by the DC gain correction. Conventional filtered back projection (FBP) filtering in the frequency domain using Fourier transform, but the filtering process uses complex number operations. To simplify the filtering process, we propose a filtering process using discrete cosine transform. In addition, the image quality of reconstructed images are improved by correcting DC gain of sinograms. To correct the DC gain, we propose to find an optimum DC weight is defined as the ratio of sinogram DC and optimum DC. Experimental results show that the proposed method gets better performance than the conventional method for phantom and clinical CT images.

• Journal of the Korean Society of Radiology
• /
• v.17 no.6
• /
• pp.819-825
• /
• 2023

In this study, among chest CT examination conditions, the tube voltage was changed to 100 and 80 kVp and the reconstruction algorithm was changed to FBP, ASIR-V, and DLIR to compare and analyze changes in examination dose and image quality. As a result, when applying ASIR-V and DLIR at a tube voltage of 100 kVp, which is lower than the existing tube voltage, the dose is lowered while achieving image quality most similar to that when applying 120 kVp and FBP. especially, DLIR reconstructed images had excellent SNR and CNR at all tube voltages. In addition, the SSIM index was analyzed to be closest to 1, showing the highest similarity to the original image. Therefore, when performing repeated chest CT examinations, the application of DLIR can reduce the examination dose by about 29.7%, which is expected to help solve some of the biggest problems with CT examinations, namely radiation exposure due to the examination.