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

The general purpose Monte Carlo N-particle radiation transport computer code (MCNP4C) was used for the simulation of x-ray spectra in diagnostic radiology and mammography. The electrons were transported until they slow down and stop in the target. Both bremsstrahlung and characteristic x-ray production were considered in this work. We focus on the simulation of various target/filter combinations to investigate the effect of tube voltage, target material and filter thickness on x-ray spectra in the diagnostic radiology and mammography energy ranges. The simulated x-ray spectra were compared with experimental measurements and spectra calculated by IPEM report number 78. In addition, the anode heel effect and off-axis x-ray spectra were assessed for different anode angles and target materials and the results were compared with EGS4based Monte Carlo simulations and measured data. Quantitative evaluation of the differences between our Monte Carlo simulated and comparison spectra was performed using student’s t-test statistical analysis. Generally, there is a good agreement between the simulated x-ray and comparison spectra, although there are systematic differences between the simulated and reference spectra especially in the K-characteristic x-rays intensity. Nevertheless, no statistically significant differences have been observed between IPEM spectra and the simulated spectra. It has been shown that the difference between MCNP simulated spectra and IPEM spectra in the low energy range is the result of the overestimation of characteristic photons following the normalization procedure. The transmission curves produced by MCNP4C have good agreement with the IPEM report especially for tube voltages of 50 kV and 80 kV. The systematic discrepancy for higher tube voltages is the result of systematic differences between the corresponding spectra. (Some figures in this article are in colour only in the electronic version) 0031-9155/04/214897+21$30.00 © 2004 IOP Publishing Ltd Printed in the UK 4897 51

Monte Carlo and experimental assessment of CT-based attenuation correction in PET

BACKGROUND
PET/CT images combining anatomic and metabolic data provide complementary information that can improve clinical task performance. PET image segmentation algorithms exploiting the multi-modal information available are still lacking.


PURPOSE
Our study aimed to assess the performance of PET and CT image fusion for gross tumor volume (GTV) segmentations of head and neck cancers (HNCs) utilizing conventional, deep learning (DL), and output-level voting-based fusions.


METHODS
The current study is based on a total of 328 histologically confirmed HNCs from six different centers. The images were automatically cropped to a 200 × 200 head and neck region box, and CT and PET images were normalized for further processing. Eighteen conventional image-level fusions were implemented. In addition, a modified U2-Net architecture as DL fusion model baseline was used. Three different input, layer, and decision-level information fusions were used. Simultaneous truth and performance level estimation (STAPLE) and majority voting to merge different segmentation outputs (from PET and image-level and network-level fusions), that is, output-level information fusion (voting-based fusions) were employed. Different networks were trained in a 2D manner with a batch size of 64. Twenty percent of the dataset with stratification concerning the centers (20% in each center) were used for final result reporting. Different standard segmentation metrics and conventional PET metrics, such as SUV, were calculated.


RESULTS
In single modalities, PET had a reasonable performance with a Dice score of 0.77 ± 0.09, while CT did not perform acceptably and reached a Dice score of only 0.38 ± 0.22. Conventional fusion algorithms obtained a Dice score range of [0.76-0.81] with guided-filter-based context enhancement (GFCE) at the low-end, and anisotropic diffusion and Karhunen-Loeve transform fusion (ADF), multi-resolution singular value decomposition (MSVD), and multi-level image decomposition based on latent low-rank representation (MDLatLRR) at the high-end. All DL fusion models achieved Dice scores of 0.80. Output-level voting-based models outperformed all other models, achieving superior results with a Dice score of 0.84 for Majority_ImgFus, Majority_All, and Majority_Fast. A mean error of almost zero was achieved for all fusions using SUVpeak , SUVmean and SUVmedian .


CONCLUSION
PET/CT information fusion adds significant value to segmentation tasks, considerably outperforming PET-only and CT-only methods. In addition, both conventional image-level and DL fusions achieve competitive results. Meanwhile, output-level voting-based fusion using majority voting of several algorithms results in statistically significant improvements in the segmentation of HNC.

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images.

/pdf/brain-mr-images-segmentation-using-3d-cnn-with-features-1qjk5etz.pdf

Brain MR images segmentation using 3D CNN with features recalibration mechanism for segmented CT generation

Positron emission tomography (PET) has a long history in the assessment of brain physiology and pathology; however, its initial use was limited to more academic and scientific settings. This changed radically with the clinical introduction of PET– computed tomography (PET-CT). PET-CT has become an integral part of the radiological armamentarium, especially in the assessment of patients with oncological or cardiovascular disorders. It has until now not found a clear role in neuroradiology. Indeed, magnetic resonance techniques have proven superior for the investigation of brain tumors and inflammatory diseases. However, some newer applications are emerging that can re-center PET-CT clearly in the neuroradiological world such as the investigation of vascular diseases.

/pdf/pet-ct-in-neuroradiology-1rk48eey1h.pdf

PET-CT in neuroradiology:

Time provides a common frame of reference for understanding different processes of change. Within the context of medical imaging, time has three different time scales to be considered: (i) microtime, (ii) mesotime, and (iii) macrotime, respectively, which span a single imaging session, distinct imaging sessions within a short period, and scans with large time gaps spanning months of even years. There has commonly been greater emphasis on the microtime and mesotime scales in both clinical practice and research, with less focus on questions that are at the macrotime scale. 

Habib Zaidi

Papers

Monte Carlo and experimental assessment of CT-based attenuation correction in PET

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images.

Brain MR images segmentation using 3D CNN with features recalibration mechanism for segmented CT generation

PET-CT in neuroradiology:

Multi-Scale Temporal Imaging: From Micro- and Meso- to Macro-scale-time Nuclear Medicine.