Most-cited articles · 2022
The 10 most-cited articles in Japanese Journal of Radiological Technology, 2022
Ranked by OpenAlex citation count on 29 October 2026, out of 164 eligible articles Japanese Journal of Radiological Technology published in 2022. Ranks are frozen; this page will not change. Number one, with 6 citations: Improvement of Motion Artifacts in Brain MRI Using Deep Learning by Simulation Training Data.
- Cohort
- 164 articles
- Listed
- Top 10 (6.1%)
- Open access
- 10 of 10
- Snapshot
- 2026-10-29
The most-cited articles published in Japanese Journal of Radiological Technology in 2022 cluster around a few themes. Deep learning applications in imaging lead the list, including the top paper, "Improvement of Motion Artifacts in Brain MRI Using Deep Learning by Simulation Training Data" by Muro and colleagues, with 6 citations, tied with Igarashi's review of trends in medical radiation protection. Radiation protection and dose evaluation also feature prominently, as do quantitative imaging and image quality assessment.
For readers, the list offers a snapshot of which topics drew the most citation attention in this journal for 2022, based on OpenAlex counts among 164 eligible articles. Citation counts are modest and reflect attention within the scholarly record rather than study quality, so the ranking should be read as an indicator of interest, not of importance.
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- 1top 0.7%
Improvement of Motion Artifacts in Brain MRI Using Deep Learning by Simulation Training Data
Isao Muro, Syuntaro Shimizu, Hikari Tsukamoto
6 citationsOpen accessdoi:10.6009/jjrt.780108OpenAlex
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PURPOSE: To test whether deep learning can be used to effectively reduce artifacts in MR images of the brain. METHODS: In this study, a large set of images with and without motion artifacts is needed for training. It is difficult to collect training data from clinical images because it requires a lot of effort and time. We have created motion artifact images of the brain by computer simulation. As an experimental study, we obtained original images for deep learning from 20 volunteers. These original images were used to create various images of different artifacts by computer simulation and these were used the input images for deep learning. The same method was used to create test images and these images were used to compare the structural similarity (SSIM) index and peak signal-to-noise ratio (PSNR) between the input images and output images using the three denoising methods. The network models used were U-shaped fully convolutional network (U-Net), denoising convolutional neural network (DnCNN) and wide inference network and 5 layers Residual learning and batch normalization…
- 2top 1.3%
Recent Trends in Medical Radiation Protection
Takayuki Igarashi
6 citationsOpen accessdoi:10.6009/jjrt.2022-1311OpenAlex
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In recent years, the field of medical radiation protection has entered an era of drastic changes. In addition to international trends, it may also be related to the increased awareness of radiation and radiation effects among the Japanese people due to the Fukushima nuclear accident in March 2011. As a result, with the revision of laws and regulations, strict control is required for medical radiation safety management and management of radiation workers. As a recent movement on radiation protection, this article reviews the changes in the threshold dose and dose limit of the lens of the eye, medical radiation safety management due to revision of medical law enforcement regulations, diagnostic reference levels, domestic and international trends regarding gonad shielding during radiography, trends toward new ICRP recommendation, and risk communication from recent trends in medical radiation protection.
- 3top 1.9%
Estimation of Eye Lens Dose during the Handling of Radiopharmaceuticals and Using X-ray Protective Goggles for Dose Reduction in Nuclear Medicine
Norikazu Matsutomo, Mitsuha Fukami, Takahisa Koike, Tomoaki Yamamoto
5 citationsOpen accessdoi:10.6009/jjrt.2022-1201OpenAlex
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【目的】本研究では,放射性医薬品を取り扱う際の水晶体被ばく線量の推定とX線防護メガネの必要性を検証した.【方法】水晶体等価線量を推定するため,線源(99mTc, 111In, 123I)を蛍光ガラス線量計から30 cmと60 cmの位置に設置して3 mm線量当量率を測定した.また,シリンジシールドと含鉛防護板,X線防護メガネ(0.07, 0.50, 0.75 mmPb)の有無で線量低減率を評価した.【結果】防護具を使用しない場合の3 mm線量当量率は,99mTcで6.13±0.13 µSv/min/GBq, 111Inで23.08±0.19 µSv/min/GBq, 123Iで11.07±0.11 µSv/min/GBqとなった.シリンジシールドと含鉛防護板を使用した場合の線量低減率はすべての放射性核種で90%以上となった.また,鉛当量0.75 mmPbのX線防護メガネの線量低減率は99mTcで68.8%,111Inで60.6%,123Iで68.1%を示した.【結語】放射性医薬品を取り扱う際の推定等価線量は水晶体の等価線量限度を超えない数値であった.鉛当量0.75 mmPbのX線防護メガネは,放射性医薬品(99mTc, 111In, 123I)を取り扱う際の水晶体被ばく線量低減に必要である.
- 4top 2.5%
Examination of the Validity of the Abdominal Circumference Measurement Method Used for Visceral Fat Evaluation Using Computed Tomography
Masato Mizui, Yuji Mizoguchi, Takao Tashiro
4 citationsOpen accessdoi:10.6009/jjrt.780302OpenAlex
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PURPOSE: or more. The evaluation of visceral fat by abdominal circumference is based on the influence of tissues other than visceral fat. The purposes of this study were to compare the abundance of visceral fat area and subcutaneous fat area and to examine the validity of estimating the visceral fat area by the abdominal circumference measurement method. METHODS: We obtained data on visceral fat area, subcutaneous fat area, and abdominal circumference of 822 subjects. Next, we investigated the correlation between the abdominal circumference and the visceral fat area, the abdominal circumference and the subcutaneous fat area, and the visceral fat area and the subcutaneous fat area of the subjects. RESULT: The abdominal circumference and visceral fat area were highly correlated, but the sum of visceral fat area and subcutaneous fat area was more highly correlated. There was a low correlation between the visceral fat area and the subcutaneous fat area. When the abdominal circumference exceeded the standard value, there was no correlation between the visceral fat area and the…
- 5top 3.1%
A Review of Current Knowledge for X-ray Energy in CT: Practical Guide for CT Technologist
Kazutaka Hoyoshi, Tomomi Ohmura, Shingo Kayano, Mitsunori Goto, Shun Muramatsu and 1 more
4 citationsOpen accessdoi:10.6009/jjrt.2022-1238OpenAlex
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In computed tomography (CT) systems, the optimal X-ray energy in imaging depends on the material composition and the subject size. Among the parameters related to the X-ray energy, we can arbitrarily change only the tube voltage. For years, the tube voltage has often been set at 120 kVp. However, since about 2000, there has been an increasing interest in reducing radiation dose, and it has led to the publication of various reports on low tube voltage. Furthermore, with the spread of dual-energy CT, virtual monochromatic X-ray images are widely used since the contrast can be adjusted by selecting the optional energy. Therefore, because of the renewed interest in X-ray energy in CT imaging, the issue of energy and imaging needs to be summarized. In this article, we describe the basics of physical characteristics of X-ray attenuation with materials and its influence on the process of CT imaging. Moreover, the relationship between X-ray energy and CT imaging is discussed for clinical applications.
- 6top 3.7%
Evaluation of Radiograph Accuracy in Skull X-ray Images Using Deep Learning
Hideyoshi Mitsutake, Haruyuki Watanabe, Aya Sakaguchi, Kiyoshi Uchiyama, Yongbum Lee and 3 more
3 citationsOpen accessdoi:10.6009/jjrt.780104OpenAlex
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PURPOSE: Accurate positioning is essential for radiography, and it is especially important to maintain image reproducibility in follow-up observations. The decision on re-taking radiographs is entrusting to the individual radiological technologist. The evaluation is a visual and qualitative evaluation and there are individual variations in the acceptance criteria. In this study, we propose a method of image evaluation using a deep convolutional neural network (DCNN) for skull X-ray images. METHOD: The radiographs were obtained from 5 skull phantoms and were classified by simple network and VGG16. The discrimination ability of DCNN was verified by recognizing the X-ray projection angle and the retake of the radiograph. DCNN architectures were used with the different input image sizes and were evaluated by 5-fold cross-validation and leave-one-out cross-validation. RESULT: Using the 5-fold cross-validation, the classification accuracy was 99.75% for the simple network and 80.00% for the VGG16 in small input image sizes, and when the input image size was general image size, simple…
- 7top 4.3%
A Study of 3D-NPS Analysis in CT Images Based on the Central Cross-section Theorem
Akihiro Narita, Masaki Ohkubo, Takahiro Fukaya, Kenichi Sakai, Yoshiyuki Noto
3 citationsOpen accessdoi:10.6009/jjrt.2022-1217OpenAlex
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PURPOSE: The noise power spectrum (NPS) of a CT scanner is commonly measured from a single noise image. However, since CT images are three-dimensional (3D) volume data, they have 3D noise characteristics (3D-NPS). In this study, we clarify the relationship among NPSs measured by various approaches in NPS analysis based on the central slice theorem. Its validity is verified by the NPS measurements using actual 3D noise data. METHODS: =0). To verify them, we compared the NPSs calculated from actual 3D noise data that were obtained using a cylindrical water phantom. RESULTS: =0). CONCLUSION: Based on the central slice theorem, we clarified the relationship among NPSs measured by various approaches in NPS analysis; it is important to understand this and then select an appropriate noise data handling and NPS measurement method.
- 8top 4.9%
Usefulness of an Ultrasound System with Automatic Bladder Urine Volume Measurement Using Artificial Intelligence Technology in Radiotherapy
Mayuri Shibata, Wataru Okada, Keisuke Sano, Kenji D. Nakamura, Yusuke Sakai and 4 more
3 citationsOpen accessdoi:10.6009/jjrt.2022-1316OpenAlex
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PURPOSE: We aimed to investigate the usefulness of iViz air ver.4 Convex (FUJIFILM, Tokyo) as a tool to determine the bladder capacity before prostate radiotherapy by comparing it with the existing BladderScan BVI 6100 (Verathon Inc., Bothell, Washington). METHODS: We investigated the usefulness of iViz air as a tool to determine the bladder capacity before prostate radiotherapy by comparing it with the current BladderScan. RESULTS: The absolute value of each error rate was approximately 30.9%±27.2% and 26.4%±18.9% for the BladderScan and iViz air, respectively, with no significant differences between the instruments (p=0.16). Evaluated by urine volume, the mean error rates for bladder volumes >50 ml were 26.9%±19.0% and 26.1%±18.5% for the Bladder Scan and iViz air, respectively, with no significant differences (p=0.56). However, the BladderScan and iViz air had significantly higher error rates of 89.5%±52.5% and 31.5%±25.1%, respectively, if the bladder volume was <50 ml (p=0.005). CONCLUSION: The iViz air has limited measurement error to confirm images, especially in limited…
- 9top 5.5%
Three-dimensional Quantitative Evaluation Method in 123I-MIBG Myocardial SPECT-CT
Yoshiaki Yasumoto, Hiromitsu Daisaki, Tadaki Nakahara, Ryoichi Ito, Isao Fujita
2 citationsOpen accessdoi:10.6009/jjrt.2023-1235OpenAlex
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PURPOSE: I-metaiodobenzylguanidine (MIBG). This study proposes a method to evaluate myocardial standardized uptake value (SUV) and assess its accuracy. METHODS: We created a 17-segment polar map of the myocardial region from single-photon emission computed tomography-computed tomography (SPECT-CT) images using a cardioliver phantom simulating the standard uptake of MIBG. We clarified the optimal reconstruction conditions with good repeatability and accuracy of quantitative values and compared them with the H/M ratio. Myocardial SUVs were evaluated from eight normal cases using our method established from the phantom experiment and compared with the H/M ratio. RESULTS: were 8.27 and 7.58, respectively. CONCLUSION: Myocardial SUV can provide quantitative values slightly closer to theoretical values than the H/M ratios. Besides, using the optimal reconstruction parameters makes it feasible to quantitatively assess myocardial uptake with good repeatability.
- 10top 6.1%
Design of X-ray Images Based on Quantitative Analysis: Predictive Model of Image Quality and Physical Quantity Factors by Multiple Regression Equation of Visual Evaluation (Scheffé’s) and Physical Quantities (Dose and Noise)
Yasuo Mochizuki
2 citationsOpen accessdoi:10.6009/jjrt.2023-1174OpenAlex
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PURPOSE: The Scheffé's method obtains the difference between pair comparisons with that of the interval scale and can judge the superiority or inferiority of the sample to be compared with no restriction in the observation image by the statistical significant difference. However, the Scheffé's method cannot be judged as a single image quality indicator. Therefore, I examined a method that can evaluate the association of average degree of preference of Scheffé's method and the physical quantities that make up the image. METHODS: This study focuses on the fact that the average degree of preference of the Scheffé's method is quantitative data on the interval scale and that multiple regression analysis is possible. In the multiple regression analysis, the average degree of preference by imaging simulated pulmonary adenocarcinoma with different exposure doses was used as the objective variable and the exposure doses and noise (standard deviation [SD]) were used as the explanatory variables. The Scheffé's method used the Nakaya's modified method. RESULTS: was -0.147, which was about 1/2…
How to read this list
The cohort is every article, review and book chapter OpenAlex attributes to Japanese Journal of Radiological Technology with publication year 2022, excluding retracted works and paratext such as editorials and errata. The top 10 by citation count are listed; the percentile is the rank divided by the cohort size. 10 of the 10 entries have an abstract in OpenAlex. Counts were read on 29 October 2026 and will not be updated on this page, so a quoted rank stays verifiable. Full rules on the methodology page.
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