bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐I‐08: CT Image Ring Artifact Reduction Based On Prior Image
Authors: Yuan C , Qi H , Chen Z , Wu S , Xu Y , Zhou L 
Published: July 2016

Purpose:In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don't work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images.Methods:The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre‐set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact‐free CT images.Results:We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp‐Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact‐free images when the dead bins rating is under 30%. The dead‐bin‐induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case.Conclusion:A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact‐free CT images feasibly and effectively.
SU‐F‐I‐09: Improvement of Image Registration Using Total‐Variation Based Noise Reduction Algorithms for Low‐Dose CBCT
Authors: Mukherjee S , Farr J , Merchant T , Yao W 
Published: July 2016

Purpose:To study the effect of total‐variation based noise reduction algorithms to improve the image registration of low‐dose CBCT for patient positioning in radiation therapy.Methods:In low‐dose CBCT, the reconstructed image is degraded by excessive quantum noise. In this study, we developed a total‐variation based noise reduction algorithm and studied the effect of the algorithm on noise reduction and image registration accuracy. To study the effect of noise reduction, we have calculated the peak signal‐to‐noise ratio (PSNR). To study the improvement of image registration, we performed image registration between volumetric CT and MV‐ CBCT images of different head‐and‐neck patients and calculated the mutual information (MI) and Pearson correlation coefficient (PCC) as a similarity metric. The PSNR, MI and PCC were calculated for both the noisy and noise‐reduced CBCT images.Results:The algorithms were shown to be effective in reducing the noise level and improving the MI and PCC for the low‐dose CBCT images tested. For the different head‐and‐neck patients, a maximum improvement of PSNR of 10 dB with respect to the noisy image was calculated. The improvement of MI and PCC was 9% and 2% respectively.Conclusion:Total‐variation based noise reduction algorithm was studied to improve the image registration between CT and low‐dose CBCT. The algorithm had shown promising results in reducing the noise from low‐dose CBCT images and improving the similarity metric in terms of MI and PCC.
SU‐F‐I‐20: Volumetric Reduction of the Corpus Callosum in Alzheimer's Disease and Mild Cognitive Impairment
Authors: Juh R , Suh T , Han J , Kim C , Oh C 
Published: July 2016

Purpose:This study investigated correlations between regional corpus callosum (CC) atrophy and cognitive measurements in AD subjects at mild disease stages with volumetry. Our aims were to replicate ROI‐based findings of reduced volumes of the CC in mild cognitive impairment (MCI) patients relative to AD and to investigate, on a voxel‐by‐voxel basis, the presence of significant correlations between CC atrophy and cognitive test scores in AD subjects.Methods:We used the VBM and cross‐sectional ROI‐based volumetry approach to conduct a detailed assessment of CC volumetric reductions in a probable AD patient (n=40) in comparison to MCI (n=40) and Subjective memory impairment (SMI) (n=12) matched for age. Statistical comparisons were performed using the general linear model.Results:The volumetric reduction of the posterior portion of the CC body, which inter‐connects cortical regions that are also early affected in AD (mean area at mid intersection, AD=510.7mm2/MCI=515.6mm2/SMI=603/9mm2, relative %ratio: AD=0.27/MCI=0.3/SMI=0.4) such as the superior temporal lobes, is also consistent with results of previous ROI‐based morphometric MRI studies. Significant CC atrophy was detected in the anterior‐superior portion of the splenium, the isthmus, the anterior and posterior portions of the CC body. Structural abnormalities of the CC splenium may be secondary to an early primary neuronal loss in AD involving parieto‐temporal neocortical regions, which are interhemispherically connected by this callosal portion.Conclusion:Our results confirm of diffuse volumetric CC reductions in the AD, and warrant further evaluation of the relevance of atrophic changes in anterior CC portions to the cognitive impairments that characterize the disorder. A cluster of significant positive correlation with MMSE scores was seen on the left anterior CC body. The VBM results reported showed that in predominantly AD subjects, foci of atrophy are present in several portions of the CC, involving the anterior‐superior portion of the splenium and the isthmus.
SU‐F‐I‐27: Measurement of SAR and Temperature Elevation During MRI Scans
Authors: Seo Y 
Published: July 2016

Purpose:The poor reliability and repeatability of the manufacturer‐reported SAR values on clinical MRI systems have been acknowledged. The purpose of this study is to not only measure SAR values, but also RF‐induced temperature elevation at 1.5 and 3T MRI systems.Methods:SAR measurement experiment was performed at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T1w inversion recovery, and T2w TSE) with imaging parameters were selected. A hydroxyl‐ethylcelluose (HEC) gelled saline phantom mimicking human body tissue was made. Human torso phantom were constructed, based on Korean adult standard anthropometric reference data (Fig.1). FDTD method was utilized to calculate the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E‐field) sensors were located inside the phantom. 55 Fiber Bragg Grating (FBG) temperature sensors (27 sensors in upper and lower cover lids, and one sensor located in the center as a reference) were located inside the phantom to measure temperature change during MRI scan (Fig.2).Results:Simulation shows that SAR value is 0.4 W/kg in the periphery and 0.001 W/kg in the center (Fig.2). One 1.5T and one of two 3T MRI systems represent that the measured SAR values were lower than MRI scanner‐reported SAR values. However, the other 3T MRI scanner shows that the averaged SAR values measured by probe 2, 3, and 4 are 6.83, 7.59, and 6.01 W/kg, compared to MRI scanner‐reported whole body SAR value (<1.5 W/kg) for T2w TSE (Table 1). The temperature elevation measured by FBG sensors is 5.2°C in the lateral shoulder, 5.1°C in the underarm, 4.7°C in the anterior axilla, 4.8°C in the posterior axilla, and 4.8°C in the lateral waist for T2w TSE (Fig.3).Conclusion:It is essential to assess the safety of MRI system for patient by measuring accurate SAR deposited in the body during clinical MRI.
SU‐F‐I‐31: Reproducibility of An Automatic Exposure Control Technique in the Low‐Dose CT Scan of Cardiac PET/CT Exams
Authors: Park M , Rosica D , Agarwal V , Di Carli M , Dorbala S 
Published: July 2016

Purpose:Two separate low‐dose CT scans are usually performed for attenuation correction of rest and stress N‐13 ammonia PET/CT myocardial perfusion imaging (PET/CT). We utilize an automatic exposure control (AEC) technique to reduce CT radiation dose while maintaining perfusion image quality. Our goal is to assess the reproducibility of displayed CT dose index (CTDI) on same‐day repeat CT scans (CT1 and CT2).Methods:Retrospectively, we reviewed CT images of PET/CT studies performed on the same day. Low‐dose CT utilized AEC technique based on tube current modulation called Smart‐mA. The scan parameters were 64 × 0.625mm collimation, 5mm slice thickness, 0.984 pitch, 1‐sec rotation time, 120 kVp, and noise index 50 with a range of 10–200 mA. The scan length matched with PET field of view (FOV) with the heart near the middle of axial FOV. We identified the reference slice number (RS) for an anatomical landmark (carina) and used it to estimate axial shift between two CTs. For patient size, we measured an effective diameter on the reference slice. The effect of patient positioning to CTDI was evaluated using the table height. We calculated the absolute percent difference of the CTDI (%diff) for estimation of the reproducibility.Results:The study included 168 adults with an average body‐mass index of 31.72 ± 9.10 (kg/m2) and effective diameter was 32.72 ± 4.60 cm. The average CTDI was 1.95 ± 1.40 mGy for CT1 and 1.97 ± 1.42mGy for CT2. The mean %diff was 7.8 ± 6.8%. Linear regression analysis showed a significant correlation between the table height and %diff CTDI. (r=0.82, p<0.001)Conclusion:We have shown for the first time in human subjects, using two same‐day CT images, that the AEC technique in low‐dose CT is reproducible within 10% and significantly depends on the patient centering.
SU‐F‐I‐41: Calibration‐Free Material Decomposition for Dual‐Energy CT
Authors: Zhao W , Xing L , Zhang Q , Xiong G , Min J 
Published: July 2016

Purpose:To eliminate tedious phantom calibration or manually region of interest (ROI) selection as required in dual‐energy CT material decomposition, we establish a new projection‐domain material decomposition framework with incorporation of energy spectrum.Methods:Similar to the case of dual‐energy CT, the integral of the basis material image in our model is expressed as a linear combination of basis functions, which are the polynomials of high‐ and low‐energy raw projection data. To yield the unknown coefficients of the linear combination, the proposed algorithm minimizes the quadratic error between the high‐ and low‐energy raw projection data and the projection calculated using material images. We evaluate the algorithm with an iodine concentration numerical phantom at different dose and iodine concentration levels. The x‐ray energy spectra of the high and low energy are estimated using an indirect transmission method. The derived monochromatic images are compared with the high‐ and low‐energy CT images to demonstrate beam hardening artifacts reduction. Quantitative results were measured and compared to the true values.Results:The differences between the true density value used for simulation and that were obtained from the monochromatic images, are 1.8%, 1.3%, 2.3%, and 2.9% for the dose levels from standard dose to 1/8 dose, and are 0.4%, 0.7%, 1.5%, and 1.8% for the four iodine concentration levels from 6 mg/mL to 24 mg/mL. For all of the cases, beam hardening artifacts, especially streaks shown between dense inserts, are almost completely removed in the monochromatic images.Conclusion:The proposed algorithm provides an effective way to yield material images and artifacts‐free monochromatic images at different dose levels without the need for phantom calibration or ROI selection. Furthermore, the approach also yields accurate results when the concentration of the iodine concentrate insert is very low, suggesting the algorithm is robust with respect to the low‐contrast scenario.
SU‐F‐I‐45: An Automated Technique to Measure Image Contrast in Clinical CT Images
Authors: Sanders J , Abadi E , Meng B , Samei E 
Published: July 2016

Purpose:To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams.Methods:An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non‐contrast enhanced chest CT clinical datasets were examined in the validation procedure.Results:The algorithm successfully measured the histograms of the four organs in both contrast and non‐contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998.Conclusion:Patient‐specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non‐enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.
SU‐F‐I‐47: Optimizing Protocols for Image Quality and Dose in Abdominal CT of Large Patients
Authors: Johnson L , Yester M 
Published: July 2016

Purpose:Newer CT scanners are able to use scout views to adjust mA throughout the scan in order to achieve a given noise level. However, given constraints of radiologist preferences for kVp and rotation time, it may not be possible to achieve an acceptable noise level for large patients. A study was initiated to determine for which patients kVp and/or rotation time should be changed in order to achieve acceptable image quality.Methods:Patient scans were reviewed on two new Emergency Department scanners (Philips iCT) to identify patients over a large range of sizes. These iCTs were set with a limit of 500 mA to safeguard against a failure that might cause a CT scan to be (incorrectly) obtained at too‐high mA. Scout views of these scans were assessed for both AP and LAT patient width and AP and LAT standard deviation in an ROI over the liver. Effective diameter and product of the scout standard deviations over the liver were both studied as possible metrics for identifying patients who would need kVp and/or rotation time changed. The mA used for the liver in the CT was compared to these metrics for those patients whose CT scans showed acceptable image quality.Results:Both effective diameter and product of the scout standard deviations over the liver result in similar predictions for which patients will require the kVp and/or rotation time to be changed to achieve an optimal combination of image quality and dose.Conclusion:Two mechanisms for CT technologists to determine based on scout characteristics what kVp, mA limit, and rotation time to use when DoseRight with our physicians’ preferred kVp and rotation time will not yield adequate image quality are described.
SU‐F‐I‐48: Variability in CT Scanning Over‐Range Across Clinical Operation
Authors: Ria F , Wilson J M , Guntzer P , Zanca F , Samei E 
Published: July 2016

Purpose:Inconsistency in the scan range for a given protocol can be a source of variability in patient dose. The purpose of this study was to determine the variability in the over‐scan length in clinical CT operation for chest and abdominopelvic (A&P) protocols.Methods:A total of 51 abdomen‐pelvis and 121 chest CT exams were randomly selected from our clinical database. A commercial dose monitoring solution was used to extract and database the total exposure area and the geometrical information related to automatically‐segmented anatomical landmarks for each target region. The data were exported off‐line for the statistical analysis. The over‐scan length (delta) was calculated as the difference between the real scanned length and ideal scanning length based on the anatomical landmarks for each target region.Results:The mean delta for abdomen‐pelvis exams was 12 mm (median 8 mm; min −191 mm; max 158 mm; standard deviation 71 mm). The average delta values at the interfaces with the chest and lower extremity regions were 69 mm and −57 mm, respectively. For chest exams, the average delta was 91 mm (median 93 mm; min 36 mm; max 190 mm; standard deviation 29 mm), and the average delta values at interfaces with the neck and abdomen regions were 26 mm and 65 mm, respectively. The percentage delta mean related to the abdomen‐pelvis and chest lengths were 3% and 45%, respectively.Conclusion:Although there is greater over‐scan in the chest region, there is considerably more variability in the over‐scan area for abdomen‐pelvis exams. Estimation of the over‐scan length must be included in the effective dose estimates, which uses different coefficients for different target region (ICRP 102). Furthermore, knowledge of over‐scan lengths and variability can guide steps to improve clinical consistency and operation.
SU‐F‐I‐51: CT/MR Image Deformation: The Clinical Assessment QA in Target Delineation
Authors: Yang C , Chen Y 
Published: July 2016

Purpose:To study the deformation effects in CT/MR image registration of head and neck (HN) cancers. We present a clinical indication in guiding and simplifying registration procedures of this process while CT images possessed artifacts.Methods:CT/MR image fusion provides better soft tissue contrast in intracranial GTV definition with artifacts. However, whether the fusion process should include the deformation process is questionable and not recommended. We performed CT/MR image registration of a HN patient with tonsil GTV and nodes delineation on Varian Velocity™ system. Both rigid transformation and deformable registration of the same CT/MR imaging data were processed separately. Physician's selection of target delineation was implemented to identify the variations. Transformation matrix was shown with visual identification, as well as the deformation QA numbers and figures were assessed.Results:The deformable CT/MR images were traced with the calculated matrix, both translation and rotational parameters were summarized. In deformable quality QA, the calculated Jacobian matrix was analyzed, which the min/mean/max of 0.73/0/99/1.37, respectively. Jacobian matrix of right neck node was 0.84/1.13/1.41, which present dis‐similarity of the nodal area. If Jacobian = 1, the deformation is at the optimum situation. In this case, the deformation results have shown better target delineation for CT/MR deformation than rigid transformation. Though the root‐mean‐square vector difference is 1.48 mm, with similar rotational components, the cord and vertebrae position were aligned much better in the deformable MR images than the rigid transformation.Conclusion:CT/MR with/without image deformation presents similar image registration matrix; there were significant differentiate the anatomical structures in the region of interest by deformable process. Though vendor suggested only rigid transformation between CT/MR assuming the geometry remain similar, our findings indicated with patient positional variations, deformation registration is needed to generate proper GTV coverage, which will be irradiated more accurately in the following boost phase.
SU‐F‐I‐62: A Dcm4chee Log Analyzer for Monitoring DICOM Network Performance
Authors: Moriyama M , Murakami Y , Ohki M , Tokumori K , Okamoto S 
Published: July 2016

Purpose:The dcm4chee is an open source software for making a high‐performance DICOM server. The process of dcm4chee is recorded in a log as text file. It takes a lot of time to read the log file for checking DICOM server performance. Therefore, we made a log analyzer for dcm4chee, which compiles the statistics on image transfer between DICOM server and imaging devices.Methods:The log analysis program was written in Perl (practical extraction and report language). ChartDirector, a chart component for creating charts for web applications was also used. The log analyzer was installed in DICOM server and invoked with a common gateway interface (CGI). The dcm4chee‐2.18.1‐mysql version using MySQL database software was used in this study. The hardware of our DICOM server for educational use was an Apple Mac mini computer (2.6GHz, Intel Core i5, 8 GB RAM) and two 6TB hard disks.Results:Users can specify the beginning and end dates to analyze in the start page of this log analyzer. Three types of output can also be chosen, which are the number of transferred images from each imaging device to the DICOM server in sequence, the total number of transferred images from each imaging device to the server in the period, and the temporal variation in free disk space of the server. These results are shown in the tabular and graph form on a web page.Conclusion:The log analyzer in this study makes it easy to get information on the usage of a dcm4chee DICOM server and should be available for the management of the PACS system using dcm4chee.
SU‐F‐I‐74: Dose Evaluation Based On Monte Carlo Simulation of Three‐Dimensional Rotational Angiography During Hepatic Transarterial Chemoembolization Procedures
Authors: Hwang Y , Lui K , Lin Y , Tsai H 
Published: July 2016

Purpose:This study was aimed to investigate the dose with patient performing three‐dimensional (3D) angiography imaging during hepatic transarterial chemoembolization (TACE) procedures.Methods:Organ doses and effective doses calculations were retrospectively performed in 88 patients (61 males and 27 females with averaged age of 65.4±12.6 years old) referred for hepatic TACE on a digital flat‐panel angiography system (Bransist safire; Shimadzu) using software (PCXMC; Helsinki, Finland) based on Monte Carlo technique. Patient information (weight and height) and projection data were also used as parameters for dose calculations. Doses were evaluated of the 26 organs in 43 projections at 5° intervals from RAO 120° to LAO 95°. 3D rotational angiography images were acquired three times (before and after contrast, as well as after chemoembolization) using the same exposure techniques (100 kV, 360 mA and 5 ms pulse width) for each patient. Effective doses and dose conversion factors (CFs) were also calculated from the Monte Carlo data.Results:Upper abdominal organs, especially for the dorsal organs, showed the higher dose. Kidney received the highest dose (45.67 mGy) during the whole 3D procedure. Averaged DAP for 88 patients was 394.67±10.85 dGycm2. Averaged effective dose during the 3D procedure were 11.33 mSv. Significant inverse linear relationship was found between effective dose and patient weight (R2 =0.90). Averaged DAP‐to‐effective dose CF were 0.027 mSvdGy−1cm−2 in our study and tend to be decreased as patient weight increased (R2=0.92).Conclusion:Effective dose for the three acquisitions in the 3D rotational angiography of TACE is comparable to the effective dose for one series in the abdominal CT. By utilizing the conversion factors, the DAPs may be useful for estimating the effective dose during 3D abdominal angiographic imaging in the future.