Diffusion tensor imaging (DTI) of human lower leg muscles: correlation between DTI parameters and muscle power with different ankle positions.

DTI parameters were significantly changed depending on the ankle joint position and type of muscle contraction.

and mean diffusivity of the soleus muscle are significantly lower in the non-contraction state as compared with isometric contraction and soleus shortening (p < 0.05). A positive correlation of the soleus muscle in the non-contraction state was seen between the maximum power and the λ


Evaluation of sodium orthovanadate as a radioprotective agent under total-body irradiation and partial-body irradiation conditions in mice.

International Journal of Radiation Biology


Medical image analysis of abdominal X-ray CT images by deep multi-layered GMDH-type neural network


Deep feedback GMDH-type neural network and its application to medical image analysis of MRI brain images


Deep multi-layered GMDH-type neural network using revised heuristic self-organization and its application to medical image diagnosis of liver cancer


Medical image diagnosis of kidney regions by deep feedback GMDH-type neural network using principal component-regression analysis


Simple noise reduction for diffusion weighted images

Our purpose in this study was to reduce the noise in order to improve the SNR of Dw images with high b-value by using two correction schemes. This study was performed with use of phantoms made from water and sucrose at different concentrations, which were 10, 30, and 50 weight percent (wt%). In noise reduction for Dw imaging of the phantoms, we compared two correction schemes that are based on the Rician distribution and the Gaussian distribution. The highest error values for each concentration with use of the Rician distribution scheme were 7.3 % for 10 wt%, 2.4 % for 30 wt%, and 0.1 % for 50 wt%. The highest error values for each concentration with use of the Gaussian distribution scheme were 20.3 % for 10 wt%, 11.6 % for 30 wt%, and 3.4 % for 50 wt%. In Dw imaging, the noise reduction makes it possible to apply the correction scheme of Rician distribution.


Medical image analysis of brain X-ray CT images by deep GMDH-type neural network

Journal of Robotics Networking and Artificial Life


Medical image diagnosis of lung cancer by deep feedback GMDH-type neural network


The 3-dimensional medical image recognition of right and left kidneys by deep GMDH-type neural network

Journal of Bioinformatics and Neuroscience


Medical image recognition of heart regions by deep multi-layered GMDH-type neural network using principal component-regression analysis


Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using principal component-regression analysis


Deep feedback GMDH-type neural network using principal component-regression analysis and its application to medical image recognition of abdominal multi-organs


Logistic GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer


Hybrid feedback GMDH-type neural network using principal component-regression analysis and its application to medical image diagnosis of lung cancer


Medical image diagnosis of liver cancer by RBF GMDH-type neural network using principal component-regression analysis


Development of cloud chamber having thin-film entrance windows and proposal of practical training for beginners using X-ray equipment and unsealed radioactive material

薄膜の入射窓を有する霧箱の開発とX線撮影装置及び非密封放射性同位元素を用いた初学者に対する実習の提案

A cloud chamber is a detector that can visualize the tracks of charged particles. Hayashi, et al. suggested a visualization experiment in which X-rays generated by diagnostic X-ray equipment were directed into a cloud chamber; however, there was a problem in that the wall of the cloud chamber scattered the incoming X-rays. In this study, we developed a new cloud chamber with entrance windows. Because these windows are made of thin film, we were able to direct the X-rays through them without contamination by scattered X-rays from the cloud chamber wall. We have newly proposed an experiment in which beta-particles emitted from radioisotopes are directed into a cloud chamber. We place shielding material in the cloud chamber and visualize the various shielding effects seen with the material positioned in different ways. During the experiment, electrons scattered in the air were measured quantitatively using GM counters. We explained the physical phenomena in the cloud chamber using Monte Carlo simulation code EGS5. Because electrons follow a tortuous path in air, the shielding material must be placed appropriately to be able to effectively block their emissions. Visualization of the tracks of charged particles in this experiment proved effective for instructing not only trainee radiological technologists but also different types of healthcare professionals.

Japanese Journal of Radiological Technology


Semi-automated Organ Segmentation Using 3-dimensional Medical Imagery through Sparse Representation

スパース表現を用いた3次元医用画像からの半自動臓器セグメンテーションアルゴリズム

This paper proposes a semi-automated organ segmentation algorithm using landmarks (LMs) from a computed tomography (CT) volume. Here, several LMs are manually defined by the user on a target organ's surface in an input volume. A patient-specific probabilistic atlas (PA) is constructed based on sparse representation obtained using training labels computed by minimizing the square error between the input and training label LMs as well as the L1 norm term. This paper presents the experimental results for the purpose of segmentation of the liver, gallbladder, and right and left kidneys, in which the proposed PA was proved to be effective in an organ of irregular shape. The average Jaccard Indices of the maximum a posteriori followed by graph cuts-based segmentation of all the target organs were 0.757 for a conventional PA, and 0.838 for the proposed PA, respectively. It was statistically confirmed that the segmentation performance using a proposed PA was superior to that using a conventional PA. We also discuss the pros and cons of the proposed PA by exploring the relationship between the organ's shape and segmentation performance.

Transactions of the Japanese Society for Medical and Biological Engineering


Hybrid multi-layered GMDH-type neural network using principal component regression analysis and its application to medical image diagnosis of liver cancer


Proposal of an experiment of the cloud chamber using the diagnostic X-ray apparatus and an analysis assisted by the simulation code

診断用X線装置を用いた霧箱実験の提案とシミュレーションコードを援用した解析

A cloud chamber is a radiation detector that can visualize the tracks of charged particles. In this study, we developed a middle-type cloud chamber for use in practical training using a diagnostic X-ray apparatus. Because our cloud chamber has a heater to vaporize ethanol and features antifogging glass, it is possible to observe the vapor trails for a long time without the need for fine adjustments. X-rays with a tube voltage of 40 kV or of 120 kV (with a 21-mm aluminum filter) were irradiated at the chamber and the various phenomena were observed. We explain these phenomena in terms of the range of electrons and/or interactions between X-rays and matter and conclude that our analysis is consistent with analysis using the Monte Carlo simulation code EGS5.


Extraction Method of Interlobar Fissure Based on Multi-Slice CT Images

胸部マルチスライスCT画像における葉間裂抽出法

葉間裂抽出は肺構造解析の基本的な手法であり,診断・治療のために活発に研究されている.しかし,間質性肺炎や重度な肺気腫などで葉間裂以外の複雑な面形状が出現する症例では問題がある.本手法は肺がん,重度な肺気腫,間質性肺炎のある症例を対象にしている.これは葉間裂の膜状の性質を利用して抽出し,粗抽出,詳細抽出,補正処理からなる.粗抽出は大きい病変を除去した肺野内で四次元曲率による画像強調と薄面化処理を用いて面形状を得て,これらから葉間裂を選択する.詳細抽出は粗描出した葉間裂を伸延する領域の面形状を強調して抽出し,接触する大きい病変周辺の面形状を解析して加える.補正処理は詳細抽出した葉間裂の穴埋めや胸壁との間隙埋めを行う.本手法の抽出結果からの距離が2mm以内に含まれるゴールドスタンダードの割合(平均±標準偏差)は正常例で91.2±3.6%,異常例で89.7±4.9%となった.ゴールドスタンダードからの距離が2mm以内に含まれる本手法の抽出結果の割合(平均±標準偏差)は正常例で95.5±3.7%,異常例で93.6±4.8%となり,良好な結果を得た.

The Transactions of the Institute of Electronics, Information and Communication Engineers D

電子情報通信学会論文誌(D)


Computer Aided Diagnosis for Osteoporosis Using Chest Multi-Slice CT Images

胸部マルチスライスCT 画像を用いた骨粗鬆症診断支援システム

急速な高齢化に伴い骨粗鬆症の罹患者は増加している.これは寝たきり状態や慢性腰痛の原因となることから大きな社会問題となっている.この克服のためには早期発見・早期治療が求められている.骨粗鬆症診断にはDXAが用いられており,補助的な役割としてQCTがある.しかし,3D QCTによる骨粗鬆症診断の有効性が高まっている.本研究では,椎体骨折や脊椎側弯症も含めた多様な三次元CT画像から骨粗鬆症を検出する診断支援システムを提案する.これは脊椎から椎体モデルを用いて椎体を抽出し,椎体の高さや海綿骨の骨密度を用いて骨折や骨密度の減少を評価する.本手法を椎体骨折や脊椎側弯症を含む526症例に適用した結果,椎体骨折の検出性能において感度99.24%,特異度98.39%と高い性能が得られ,正常症例の5568椎体について海綿骨の骨密度測定を実現した.また,正常8症例で全身DXAの骨密度と椎体の海綿骨の平均骨密度との比較を行った結果,相関係数の二乗値が0.8288と高い相関が得られた.

電子情報通信学会論文誌(D)


Medical image diagnosis of lung cancer by multi-layered GMDH-type neural network self-selecting functions


Medical image diagnosis of liver cancer by hybrid feedback GMDH-type neural network using heuristic self-organization


Medical image diagnosis of liver cancer by feedback GMDH-type neural network using knowlege base


Gender disparities in the association between epicardial adipose tissue volume and coronary atherosclerosis: A 3-dimensional cardiac computed tomography imaging study in Japanese subjects.

Growing evidence suggests that epicardial adipose tissue (EAT) may contribute to the development of coronary artery disease (CAD). In this study, we explored gender disparities in EAT volume (EATV) and its impact on coronary atherosclerosis. The study population consisted of 90 consecutive subjects (age: 63 ± 12 years; men: 47, women: 43) who underwent 256-slice multi-detector computed tomography (MDCT) coronary angiography. EATV was measured as the sum of cross-sectional epicardial fat area on CT images, from the lower surface of the left pulmonary artery origin to the apex. Subjects were segregated into the CAD group (coronary luminal narrowing > 50%) and non-CAD group. EATV/body surface area (BSA) was higher among men in the CAD group than in the non-CAD group (62 ± 13 vs. 33 ± 10 cm3/m2, p < 0.0001), but did not differ significantly among women in the 2 groups (49 ± 18 vs. 42 ± 9 cm3/m2, not significant). Multivariate logistic analysis showed that EATV/BSA was the single predictor for >50% coronary luminal narrowing in men (p < 0.0001). Predictors excluded were age, body mass index, hypertension, diabetes mellitus, and hyperlipidemia. Increased EATV is strongly associated with coronary atherosclerosis in men.


Medical Image Diagnosis of Liver Cancer by Multi-layered GMDH-type Neural Network Using Knowledge Base


Medical Image Diagnosis of Lung Cancer by Feedback GMDH-type Neural Network Self-selecting Neural Network Architectuer


Feedback GMDH-type Neural Network and Its Application to Medical Image Analysis of Liver Cancer

International Journal of Innovative Computing, Information and Control


Usefulness of transcatheter arterial embolization prior to excision of hypervascular musculoskeletal tumors.

The objective of this study was to evaluate the usefulness of transcatheter arterial embolization prior to surgical excision of musculoskeletal tumors. We reviewed the records of nine patients (3 females and 6 males) who received arterial embolization prior to excision of musculoskeletal tumors in our hospital from December 2009 to April 2010. We evaluated tumor region, size, histopathology, feeding artery, embolic material, and blood loss during surgery. We compared the actual amount of intraoperative bleeding with arterial embolization to estimated amounts of bleeding without embolization predicted by three orthopedic surgeons. Arterial embolization was performed on the same day or within 5 days before surgery. Operations were performed as planned in all patients without serious complications. The amount of intraoperative bleeding was 35-4200 mL and there was significantly less bleeding with arterial embolization compared with the estimated amounts (p<0.01). Our results show that arterial embolization prior to resection of hypervascular musculoskeletal tumors reduces the amount of bleeding during surgery and contributes to patient safety.

The Journal of Medical Investigation : JMI


Medical image diagnosis of lung cancer by revised GMDH-type neural network using various kinds of neurons


Using the MDCT thick slab MinIP method for the follow-up of pulmonary emphysema

The purpose of this study was to evaluate the usefulness of thick slab minimum intensity projection (MinIP) as a follow-up method in patients with pulmonary emphysema. This method was used to determine the presence or absence of changes over time in the lung field based on multi-detector-row CT (MDCT) data. Among patients diagnosed with pulmonary emphysema who underwent 16-MDCT (slice thickness, 1 mm) twice at an interval of 6 months or more, 12 patients without changes in the lung field and 14 with clear changes in the lung field were selected as subjects. An image interpretation experiment was performed by five image interpreters. Pulmonary emphysema was followed up using two types of thick slab MinIP (thick slab MinIP 1 and 2) and multi-planar reformation (MPR), and the results of image interpretation were evaluated by receiver operating characteristic (ROC) analysis. In addition, the time required for image interpretation was compared among the three follow-up methods. The area under the ROC curve (Az) was 0.794 for thick slab MinIP 1, 0.778 for the thick slab MinIP 2, and 0.759 for MPR, showing no significant differences among the three methods. Individual differences in each item were significantly more marked for MPR than for thick slab MinIP. The time required for image interpretation was around 18 seconds for thick slab MinIP 1, 11 seconds for thick slab MinIP 2, and approximately 127 seconds for MPR, showing significant differences among the three methods. There were no significant differences in the results of image interpretation regarding the presence or absence of changes in the lung fields between thick slab MinIP and MPR. However, thick slab MinIP showed a shorter image interpretation time and smaller individual differences in the results among image interpreters than MPR, suggesting the usefulness of this method for determining the presence or absence of changes with time in the lung fields of patients with pulmonary emphysema.


Medical image diagnosis of liver cancer using a neural network and artificial intelligence

Journal of Advanced Computational Intelligence and Intelligent Informatics


Measurements of multi-detector CT surface dose distributions using a film dosimeter and chest phantom

This paper uses film dosimetry to investigate the relationship between multiple scan parameters of multidetector CT with automatic exposure control (AEC) and the surface dose distribution produced on a chest phantom. The characteristics of the film used in the film dosimeter were evaluated with regard to linearity, relative film response, and directional dependence. Measurements with an ionization chamber dosimeter and a water phantom were used to evaluate the accuracy of the film dosimeter measurements and to validate the dose profile measurements while changing the tube current, detector dimensions and pitch. When using AEC, the surface dose distribution on the chest phantom was analyzed while changing the detector dimensions and pitch. The linearity, relative film response, and directional dependence of the film were established. The measurement difference between the film dosimeter and ionization chamber dosimeter was within +/- 5% and the dose profile measurement results were validated. It was found that the surface dose distribution changed helically in the direction of the body axis depending on the scan parameters and the phantom. Using a film dosimeter, the relationship between various multidetector CT scan parameters and the surface dose distribution on a chest phantom was investigated and clarified.


Feedback GMDH-type neural network algorithm and its application to medical image analysis of cancer of the liver


Radiographic comparison between male and female patients with lumbar spondylolysis.

We studied the lumbar spines of 117 adults (39 women and 78 men) with spondylolysis unrelated to low back pain using multidetector computed tomography (CT). Of the 117 subjects with spondylolysis, including five with multiple-level spondylolysis, there were 124 vertebrae with spondylolysis. In adult lumbar spines with unilateral spondylolysis, there was no significant difference between the incidence of spondylolisthesis in female and male subjects. However, in those with bilateral spondylolysis, there was a significantly higher incidence of spondylolisthesis in female subjects (90.9%) than in males (66.2%). Furthermore, females with bilateral spondylolysis had significant more slippage than males. Lumbar index and lumbar lordosis were not significantly different between male and female subjects, and did not significantly correlate with slippage. In conclusion, to treat acute spondylolysis in adolescents, it is important to obtain bony union at least unilaterally, especially in female subjects, to prevent further slippage.


Three-dimensional medical image recognition of the cancer of the liver by a revised radial basis function (RBF) neural network algorithm


Three-dimensional medical image analysis of the heart by the revised GMDH-type neural network self-selecting optimum nrural network architecture


Medical image recognition of abdominal multi-organs by RBF GMDH-type neural network

International Journal of Innovative Computing, Information and Control


DICOM画像の個人情報保護のための匿名化システム

DICOM画像の個人情報保護のための匿名化システム

医用画像を二次利用する場合には,医療施設の倫理審査委員会に申請して認可を得た後に個人情報の保護を行う必要がある.これには患者へのインフォームドコンセントや許諾を得た患者の個人情報の識別を防止する匿名化が求められている.匿名化の対象となる情報は医療施設の倫理審査委員会の指針に沿って実施する必要があり,これは医療施設で異なるのが現状である.そこで,多数の医療施設に適用でき,かつ大規模なDICOM画像を効率的に匿名化できるシステムの開発が求められている.本論文では,医療施設の匿名化ポリシを柔軟に設定でき,大規模なDICOM画像をオンライン処理で匿名化できるシステムを研究開発する.このシステムを八つの医療施設で臨床運用してその有効性を示す.

The Transactions of the Institute of Electronics, Information and Communication Engineers D

電子情報通信学会論文誌(D)


Multi-Layered GMDH-type Neural Network Self-Selecting Optimum Neural Network Architecture and Its Application to 3-Dimensional Medical Image Recognition of Blood Vessels


Postprocessing technique with MDCT data improves the accuracy of the detection of lung nodules

The aim of this study was to determine whether postprocessing techniques could improve the accuracy of detecting lung nodules. A total of 154 segmented lung volumes of multidetector-row computed tomography (MDCT) data were the subject of the study. Lung nodules were present in 88 volumes and absent in 66 volumes. We prepared four groups: (1) 7- or 10-mm thick-section axial images; (2) 1-mm thin-section axial images; (3) sliding slab maximum intensity projection (MIP) images with a slab thickness of 15 mm; and (4) sliding slab volume rendering (VR) images with a slab thickness of 15 mm. Sixteen physicians reviewed each group in interactive cine mode. The observers' performance in the detection of lung nodule was evaluated by receiver operating characteristic (ROC) analysis. The observers' performance of the MIP and VR groups was significantly better than in other two groups. There was no significant difference statistically between the thin and thick groups. The detectability of lung nodules is improved with the use of sliding slab MIP and VR using thin-section image data. Thin-section volume data are essential for improving diagnostic accuracy, but observation of thin-section images without utilization of image-processing techniques dose not improve diagnostic accuracy.


Logistic GMDH-type Neural Network and Its Application to the Identification of the X-ray Film Characteristic Curve


Multi-layered GMDH-type Neural Network with Radial Basis Functions and Its Application to the 3-dimensional Medical Image Recognition of the Liver

Journal of Advanced Computational Intelligence and Intelligent Informatics


Medical Image Recognition of the Brain by Revised GMDH-type Neural Network Algorithm with a Feedback Loop


Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network


Three dimensional medical image recognition of lungs by revised GMDH-type neural network algorithm

International Journal of Computer Assisted Radiology and Surgery


Socio-economical effects of film-less PACS; comparison of pre- and post-film-less operation


Revised GMDH-type Neural Networks using AIC or PSS Criterion and Their Application to the Medical Image Recognition

Journal of Advanced Computational Intelligence and Intelligent Informatics


Huang, L., Ogushi, F., Tani, K., Ogawa, H., Kawano, T., Endo, T., Izumi, K., Ueno, J., Nishitani, H. and Sone, S. Thrombin Promotes Fibroblast Proliferation during the Early Stages of Experimental Radiation Pneumonitis. Radiat. Res. 156, 45-52 (2001). To clarify the role of thrombin in the pathogenesis of radiation-induced pneumonitis, we measured the thrombin activity and fibroblast growth-inducing activity in bronchoalveolar lavage fluid obtained from the irradiated lungs of rats at 1, 2, 4, 8 and 18 weeks after irradiation. Thrombin activity was not detected in the bronchoalveolar lavage fluid from unirradiated rats, but the bronchoalveolar lavage fluid from irradiated rats showed significantly increased thrombin activity which reached a maximum at 4 weeks after treatment. Higher fibroblast growth-inducing activity was detected in the bronchoalveolar lavage fluid from irradiated rats at 4 and 18 weeks than in fluid from unirradiated rats. Bronchoalveolar lavage fluid from irradiated rats that were pretreated with the thrombin inhibitors antithrombin III and argatroban showed significantly inhibited fibroblast growth-inducing activity and thrombin activity at 4 weeks. However, these thrombin inhibitors did not inhibit fibroblast growth-inducing activity in bronchoalveolar lavage fluid from irradiated rats at 18 weeks. Purified rat thrombin similarly induced proliferation of fibroblasts derived from irradiated and unirradiated rats. These findings suggest that thrombin may play an important role as a fibroblast growth-inducing factor during the early stages of radiation pneumonitis.


Evaluation of multi-vendor PACS in the wards --- performance and users' behavior


Radiation Complications Following Breast Conserving Therapy


回転デジタルX線撮影装置を用いたコーンビームC --- 肺野および骨病変に対する初期臨床経験


Complexities encountered in reconstructing 3D images of sellar and parasellar lesions from CT data for surgical planning


Undergraduate Radiology Education Utilizing WWW Server-Client System


Multimedia Based Teaching File for Radiological Cases Diagnosed with 3D Images and Models from CT and MR Modalities


Ectopic Gastric Mucosa in the Upper Esophagus --- Prevalence and Radiologic Findings


Three Dimensional Longitudinal Dissection View of Hollow Viscus


Diagnostic Ability of Computer Recreated Images of Pathological Lesions of the Alimentary System

Computer Applicatons to Assist Radiology


Ectopic Gastric Mucosa in the Upper Esophagus --- Detection and Radiographic Findings


Distribution of DNA content per mucosa cell nucleus in multiple gastric cancers and their surroundings

多発胃癌の胃粘膜内細胞DNA量分布


1. 十二指腸悪性リンパ腫と早期胃癌を合併した1例

1. 十二指腸悪性リンパ腫と早期胃癌を合併した1例


MDCTのボリュームデータを用いた肺結節の検出法の検討

MDCTのボリュームデータを用いた肺結節の検出法の検討

The purpose of this study is to determine if combination of adequate postprocessing techniques and thin section image data from MDCT could improve the accuracy of detection of lung nodules. Readers' performance for the nodule detection was evaluated by ROC analysis. The combination of postprocessing techniques (STS-MIP or STS-VR) using thin section image data from MDCT improved the accuracy of detection of lung nodules significantly. There is no statistically significant difference in the detectability of lung nodules between the scrolling through thin section images and the scrolling through thick section images.

MDCTで撮像された胸部CTにおいて肺野の小結節を対象に，その存在診断における薄いスライス厚のボリュームデータの有効な利用観察方法について検討した．Thick section (10mm)，thin section (1mm)のaxial像および15mmスラブ厚でのインタラクティブなスライディングを用いたMIP法とVR法で検出能の違いを比較するための読影実験を行い，ROC解析を用い検討した．MIP法やVR法での観察が有用であり，thin sectionのみの観察では検出能は向上しなかった．


Three Dimensional Dissection View of the Urinary Bladder

International Journal of Computer Assisted Radiology and Surgery


オムニパークの有用性に関する徳島地区多施設共同研究

オムニパークの有用性に関する徳島地区多施設共同研究


点滴静注尿路造影におけるイオパミロン150の使用経験

点滴静注尿路造影におけるイオパミロン150の使用経験

The Japanese journal of clinical and experimental medicine


Detecting Lung Cancer Symptoms with Analogic CNN Algorithms Based on a Constrained Diffusion Template

In this article, a new type of diffusion template and an analogic CNN algorithm using this diffusion template for detecting some lung cancer symptoms in X-ray films are proposed. The performance of the diffusion template is investigated and our CNN algorithm is verified to detect some key lung cancer symptoms, successfully.

本研究では，新しいタイプの拡散テンプレートと，その拡散テンプレートを利用したX線画像の肺癌部分検出セルラ·ニューラル·ネットワークのアルゴリズムを提案している．拡散テンプレートの特徴を詳細に調査し，さらに，本手法が肺癌部分を効果的に抽出できることを確認している．

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences


Parasitic Eosinophilic Granuloma of the Stomach Resembling a Submucosal Tumor

The American Journal of Gastroenterology