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Japanese Journal of Medical Physics

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https://www.readbyqxmd.com/read/28442656/series-basic-exercises-using-excel-1
#1
REVIEW
Takeyuki Hashimoto
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442655/series-practical-evaluation-of-clinical-image-quality-4-determination-of-image-quality-in-digital-radiography-system
#2
REVIEW
Reiji Katayama
Recently, for medical imaging, digital radiography systems are widely used in clinical practices. However, a study in the past reported that a patient radiation exposure level by digital radiography is in fact not lower than that by analog radiography system. High level of attention needs to be paid for over-exposure when using the conventional analog radiography with a screen and a film, as it results in high density of the film. However, for digital radiography systems, since the automatic adjusting function of image density is equipped with them, no attention for radiation dose need to be paid...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442654/utility-of-vmat-aspect-of-clinical-application
#3
REVIEW
Akihiro Haga
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442653/handling-density-conversion-in-tps
#4
REVIEW
Tomonori Isobe, Yutaro Mori, Hideyuki Takei, Eisuke Sato, Kiichi Tadano, Daisuke Kobayashi, Tetsuya Tomita, Takeji Sakae
Conversion from CT value to density is essential to a radiation treatment planning system. Generally CT value is converted to the electron density in photon therapy. In the energy range of therapeutic photon, interactions between photons and materials are dominated with Compton scattering which the cross-section depends on the electron density. The dose distribution is obtained by calculating TERMA and kernel using electron density where TERMA is the energy transferred from primary photons and kernel is a volume considering spread electrons...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442652/an-introduction-to-optimization-theory
#5
REVIEW
Jun'ichi Kotoku
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442651/basics-of-monte-carlo-simulation-focusing-on-dose-to-medium-and-dose-to-water
#6
REVIEW
Kiichi Tadano, Tomonori Isobe, Eisuke Sato, Hideyuki Takei, Daisuke Kobayashi, Yutaro Mori, Tetsuya Tomita, Takeji Sakae
Treatment planning systems with highly accurate dose calculation algorithms such as Monte-Carlo method and linear Boltzmann transport equation are becoming popular thanks to a development of the computer technology. These algorithms use new concepts, dose-to-medium and dose-to-water. However, introducing these concepts can cause confusion in clinical sites. Basic knowledges about Monte-Carlo simulation and other corresponding algorithms were explained in this article such as the principles, the parameters and words of caution...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442650/evolution-of-dose-calculation-algorithms-for-external-beam-treatment-planning
#7
REVIEW
Nanako Hirai, Sayaka Sato
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442649/the-handling-of-the-medical-device-program-with-pharmaceutical-and-medical-device-act
#8
Yusuke Shimizu
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28442648/preface-to-the-special-issue-radiation-treatment-planning-system
#9
EDITORIAL
Teiji Nishio
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428500/mini-lecture-on-x-ray-computed-tomography-methods-for-evaluating-radiation-dose
#10
Kosuke Matsubara
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428499/series-utilization-of-differential-equations-and-methods-for-solving-them-in-medical-physics-4
#11
Kenya Murase
Partial differential equations are often used in the field of medical physics. In this (final) issue, the methods for solving the partial differential equations were introduced, which include separation of variables, integral transform (Fourier and Fourier-sine transforms), Green's function, and series expansion methods. Some examples were also introduced, in which the integral transform and Green's function methods were applied to solving Pennes' bioheat transfer equation and the Fourier series expansion method was applied to Navier-Stokes equation for analyzing the wall shear stress in blood vessels...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428498/medical-applications-of-the-phits-code-3-user-assistance-program-for-medical-physics-computation
#12
Takuya Furuta, Shintaro Hashimoto, Tatsuhiko Sato
DICOM2PHITS and PSFC4PHITS are user assistance programs for medical physics PHITS applications. DICOM2PHITS is a program to construct the voxel PHITS simulation geometry from patient CT DICOM image data by using a conversion table from CT number to material composition. PSFC4PHITS is a program to convert the IAEA phase-space file data to PHITS format to be used as a simulation source of PHITS. Both of the programs are useful for users who want to apply PHITS simulation to verification of the treatment planning of radiation therapy...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428497/series-practical-evaluation-of-clinical-image-quality-2-image-quality-measurements-for-digital-radiography-systems
#13
REVIEW
Reiji Katayama
In recent years, the manuals and data analysis tools to evaluate the basic imaging properties of medical imaging systems, such as digital radiography system, CT, and MRI, are easily available. For the image quality evaluation of digital radiography systems, special measurement system, such as a microdensitometer, required for the analysis of analog radiography system, is not needed. This enabled anyone to perform the evaluation of digital radiography system.On the other hand, to make accurate measurements, obtaining appropriate image data is a must...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428496/outcome-prediction-after-radiotherapy-with-medical-big-data
#14
REVIEW
Taiki Magome
Data science is becoming more important in many fields. In medical physics field, we are facing huge data every day. Treatment outcomes after radiation therapy are determined by complex interactions between clinical, biological, and dosimetrical factors. A key concept of recent radiation oncology research is to predict the outcome based on medical big data for personalized medicine. Here, some reports, which are analyzing medical databases with machine learning techniques, were reviewed and feasibility of outcome prediction after radiation therapy was discussed...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428495/applications-of-machine-learning-for-radiation-therapy
#15
REVIEW
Hidetaka Arimura, Takahiro Nakamoto
Radiation therapy has been highly advanced as image guided radiation therapy (IGRT) by making advantage of image engineering technologies. Recently, novel frameworks based on image engineering technologies as well as machine learning technologies have been studied for sophisticating the radiation therapy. In this review paper, the author introduces several researches of applications of machine learning for radiation therapy. For examples, a method to determine the threshold values for standardized uptake value (SUV) for estimation of gross tumor volume (GTV) in positron emission tomography (PET) images, an approach to estimate the multileaf collimator (MLC) position errors between treatment plans and radiation delivery time, and prediction frameworks for esophageal stenosis and radiation pneumonitis risk after radiation therapy are described...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428494/machine-learning-for-computer-aided-diagnosis
#16
REVIEW
Mitsutaka Nemoto, Yoshitaka Masutani, Yukihiro Nomura, Shohei Hanaoka, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ootomo
Machine learning algorithms are to analyze any dataset to extract data-driven model, prediction rule, or decision rule from the dataset. Various machine learning algorithms are now used to develop high-performance medical image processing systems such as computer-aided detection (CADe) system which detects clinically significant objects from medical images and computer-aided diagnosis (CADx) system which quantifies malignancy of manually or automatically detected clinical objects. In this paper, we introduce some applications of machine learning algorithms to the development of medical image processing system...
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428493/segmentation-classification-and-high-resolution-of-image-by-machine-learning
#17
REVIEW
Takeshi Nagata
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428492/questionnaire-survey-of-japanese-medical-physicists-for-working-conditions-in-2014
#18
Naoki Tohyama, Hiroyuki Okamoto, Teiji Nishio
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428491/an-introduction-to-machine-learning
#19
REVIEW
Jun'ichi Kotoku
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
https://www.readbyqxmd.com/read/28428490/machine-learning-leading-the-way-for-medical-physics-preface-to-the-special-issue
#20
EDITORIAL
Akihiro Haga
No abstract text is available yet for this article.
2016: Japanese Journal of Medical Physics
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