There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

NOTE The report of the Committee without its annexes appears as Official Records of the General Assembly, Sixty-third Session, Supplement No. 46. The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. The country names used in this document are, in most cases, those that were in use at the time the data were collected or the text prepared. In other cases, however, the names have been updated, where this was possible and appropriate, to reflect political changes. Scientific Annexes Annex A. Medical radiation exposures Annex B. Exposures of the public and workers from various sources of radiation INTROdUCTION 1. In the course of the research and development for and the application of atomic energy and nuclear technologies, a number of radiation accidents have occurred. Some of these accidents have resulted in significant health effects and occasionally in fatal outcomes. The application of technologies that make use of radiation is increasingly widespread around the world. Millions of people have occupations related to the use of radiation, and hundreds of millions of individuals benefit from these uses. Facilities using intense radiation sources for energy production and for purposes such as radiotherapy, sterilization of products, preservation of foodstuffs and gamma radiography require special care in the design and operation of equipment to avoid radiation injury to workers or to the public. Experience has shown that such technology is generally used safely, but on occasion controls have been circumvented and serious radiation accidents have ensued. 2. Reviews of radiation exposures from accidents have been presented in previous UNSCEAR reports. The last report containing an exclusive chapter on exposures from accidents was the UNSCEAR 1993 Report [U6]. 3. This annex is aimed at providing a sound basis for conclusions regarding the number of significant radiation accidents that have occurred, the corresponding levels of radiation exposures and numbers of deaths and injuries, and the general trends for various practices. Its conclusions are to be seen in the context of the Committee's overall evaluations of the levels and effects of exposure to ionizing radiation. 4. The Committee's evaluations of public, occupational and medical diagnostic exposures are mostly concerned with chronic exposures of …

sources and effects of ionizing radiation

Monte Carlo codes for use in therapeutic nuclear medicine

Abstract We aimed to construct a prediction model based on computed tomography (CT) radiomics features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A total of 1110 patients were studied from a publicly available dataset with 4-class severity scoring performed by a radiologist (based on CT images and clinical features). The entire lungs were segmented and followed by resizing, bin discretization and radiomic features extraction. We utilized two feature selection algorithms, namely bagging random forest (BRF) and multivariate adaptive regression splines (MARS), each coupled to a classifier, namely multinomial logistic regression (MLR), to construct multiclass classification models. The dataset was divided into 50% (555 samples), 20% (223 samples), and 30% (332 samples) for training, validation, and untouched test datasets, respectively. Subsequently, nested cross-validation was performed on train/validation to select the features and tune the models. All predictive power indices were reported based on the testing set. The performance of multi-class models was assessed using precision, recall, F1-score, and accuracy based on the 4 × 4 confusion matrices. In addition, the areas under the receiver operating characteristic curves (AUCs) for multi-class classifications were calculated and compared for both models. Using BRF, 23 radiomic features were selected, 11 from first-order, 9 from GLCM, 1 GLRLM, 1 from GLDM, and 1 from shape. Ten features were selected using the MARS algorithm, namely 3 from first-order, 1 from GLDM, 1 from GLRLM, 1 from GLSZM, 1 from shape, and 3 from GLCM features. The mean absolute deviation, skewness, and variance from first-order and flatness from shape, and cluster prominence from GLCM features and Gray Level Non Uniformity Normalize from GLRLM were selected by both BRF and MARS algorithms. All selected features by BRF or MARS were significantly associated with four-class outcomes as assessed within MLR (All p values &lt; 0.05). BRF + MLR and MARS + MLR resulted in pseudo-R 2 prediction performances of 0.305 and 0.253, respectively. Meanwhile, there was a significant difference between the feature selection models when using a likelihood ratio test ( p value = 0.046). Based on confusion matrices for BRF + MLR and MARS + MLR algorithms, the precision was 0.856 and 0.728, the recall was 0.852 and 0.722, whereas the accuracy was 0.921 and 0.861, respectively. AUCs (95% CI) for multi-class classification were 0.846 (0.805–0.887) and 0.807 (0.752–0.861) for BRF + MLR and MARS + MLR algorithms, respectively. Our models based on the utilization of radiomic features, coupled with machine learning were able to accurately classify patients according to the severity of pneumonia, thus highlighting the potential of this emerging paradigm in the prognostication and management of COVID-19 patients. 

/pdf/high-dimensional-multinomial-multiclass-severity-scoring-of-30mc4v3z.pdf

High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms

Comparative methods for 18F-FDG PET-based delineation of target volumes in non-small-cell lung cancer

OBJECTIVE: Cardiac positron emission tomography (PET)/CT imaging is a noninvasive procedure allowing the assessment of coronary artery disease (CAD). CT-based attenuation correction of PET data is essential for accurate quantitative analysis in PET/CT imaging. Coronary artery calcium scoring CT (CaScCT) is used as a noninvasive tool for the diagnosis of atherosclerosis in patients with medium risk for CAD. In addition to the CaScCT examination, current cardiac rest/stress NH3 or (1)F-fluorodeoxyglucose viability PET/CT protocols incorporate a correlated low-dose CT scan for attenuation correction purposes (ACCT). As a result, the patient receives a non-negligible radiation dose. The aim of this study is to evaluate the possibility of using CaScCT images for AC of myocardial rest/stress/viability PET data with the aim of reducing patient dose. METHODS: Since in cardiac PET/CT protocols, the CaScCT examination is usually reconstructed using a small field-of-view, the CaScCT data were reconstructed again with extended field-of-view (ExCaScCT) and used for AC of the corresponding PET data. The feasibility study was performed using 10 patients including four NH3 perfusion and six (1)F-fluorodeoxyglucose viability examinations acquired on the Biograph TP 64 PET/CT scanner. The assessment of PET images corrected using both ACCT and ExCaScCT images was carried out through qualitative assessment performed by an expert nuclear medicine specialist in addition to the regression analysis and the Bland-Altman plots, and 20-segment myocardial bull's eye view analysis. RESULTS: Despite the good agreement between PET images corrected using ACCT and ExCaScCT images as expressed by the correlation coefficient and slope of the regression line in viability (0.949 +/- 0.041 and 0.994 +/- 0.124) and stress perfusion examinations (0.944 +/- 0.008 and 0.968 +/- 0.055), the rest perfusion examinations had weak correlation (0.454 +/- 0.203 and 0.757 +/- 0.193). This is attributed to the fact that the CaScCT scan is performed immediately after the stress/viability ACCT in our protocol that leads to a small misalignment between the CaScCT and stress/viability ACCT images, whereas there is a large misalignment between the CaScCT and rest ACCT images. The bull's eye view analysis showed that the difference between the uptake values was larger in the inferior wall because of diaphragm motion. CONCLUSION: Our preliminary results seem to suggest that the calcium score study could be used for attenuation correction of cardiac PET images, thus allowing the elimination of ACCT in viability and stress perfusion studies and as such reduce patient dose.

Coronary calcium score scan-based attenuation correction in cardiovascular PET imaging.

Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image reconstruction can substantially prevent kinetic parameter error propagation either from erroneous kinetic modelling, inter-frame motion or emission/transmission mismatch. Furthermore, we demonstrate the benefits of TOF in parameter estimation when conventional post-reconstruction (3D) methods are used and compare the potential improvements to direct 4D methods. Further improvements could possibly be achieved in the future by combining TOF direct 4D image reconstruction with adaptive kinetic models and inter-frame motion correction schemes.

/pdf/impact-of-time-of-flight-on-indirect-3d-and-direct-4d-k57qfxwfb1.pdf

Habib Zaidi

Papers

Monte Carlo codes for use in therapeutic nuclear medicine

High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms

Comparative methods for 18F-FDG PET-based delineation of target volumes in non-small-cell lung cancer

Coronary calcium score scan-based attenuation correction in cardiovascular PET imaging.

Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data