野村 行弘

PURPOSE: For the development of computer-assisted detection (CAD) software using voxel-based classification, gold standards defined by pixel-by-pixel painting, called painted gold standards, are desirable. However, for radiologists who define gold standards, a simplified method of definition is desirable. One of the simplest methods of defining gold standards is a spherical region, called a spherical gold standard. In this study, we investigated whether spherical gold standards can be used as an alternative to painted gold standards for computerized detection using voxel-based classification. MATERIALS AND METHODS: The spherical gold standards were determined by the center of gravity and the maximum diameter. We compared two types of gold standard, painted gold standards and spherical gold standards, by two types of CAD software using voxel-based classification. RESULTS: The time required to paint the area of one lesion was 4.7-6.5 times longer than the time required to define a spherical gold standard. For the same performance of the CAD software, the number of training cases required for the spherical gold standard was 1.6-7.6 times that for the painted gold standards. CONCLUSION: Spherical gold standards can be used as an alternative to painted gold standards for the computerized detection of lesions with simple shapes.

© 2018 Association for Computing Machinery. The reading workload for radiologists is increasing because the numbers of examinations and images per examination are increasing due to the technical progress on imaging modalities such as computed tomography and magnetic resonance imaging. A computer-assisted detection (CAD) system based on machine learning is expected to assist radiologists. The preliminary results of a multi-institutional study indicate that the performance of the CAD system for each institution improved using training data of other institutions. This indicates that transfer learning may be useful for developing the CAD systems among multiple institutions. In this paper, we focus on transfer learning without sharing training data due to the need to protect personal information in each institution. Moreover, we raise a problem of negative transfer in CAD system and propose an algorithm for inhibiting negative transfer. Our algorithm provides a theoretical guarantee for managing CAD software in terms of transfer learning and exhibits experimentally better performance compared to that of the current algorithm in cerebral aneurysm detection.

BACKGROUND: The usefulness of computer-assisted detection (CAD) for detecting cerebral aneurysms has been reported; therefore, the improved performance of CAD will help to detect cerebral aneurysms. PURPOSE: To develop a CAD system for intracranial aneurysms on unenhanced magnetic resonance angiography (MRA) images based on a deep convolutional neural network (CNN) and a maximum intensity projection (MIP) algorithm, and to demonstrate the usefulness of the system by training and evaluating it using a large dataset. STUDY TYPE: Retrospective study. SUBJECTS: There were 450 cases with intracranial aneurysms. The diagnoses of brain aneurysms were made on the basis of MRA, which was performed as part of a brain screening program. FIELD STRENGTH/SEQUENCE: Noncontrast-enhanced 3D time-of-flight (TOF) MRA on 3T MR scanners. ASSESSMENT: In our CAD, we used a CNN classifier that predicts whether each voxel is inside or outside aneurysms by inputting MIP images generated from a volume of interest (VOI) around the voxel. The CNN was trained in advance using manually inputted labels. We evaluated our method using 450 cases with intracranial aneurysms, 300 of which were used for training, 50 for parameter tuning, and 100 for the final evaluation. STATISTICAL TESTS: Free-response receiver operating characteristic (FROC) analysis. RESULTS: Our CAD system detected 94.2% (98/104) of aneurysms with 2.9 false positives per case (FPs/case). At a sensitivity of 70%, the number of FPs/case was 0.26. DATA CONCLUSION: We showed that the combination of a CNN and an MIP algorithm is useful for the detection of intracranial aneurysms. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:948-953.

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

PURPOSE: The anatomical anomaly of the number of vertebral bones is one of the major anomalies in the human body, which can cause confusion of the spinal level in, for example, surgery. The aim of this study is to develop an automatic detection system for this type of anomaly. METHODS: We utilized our previously reported anatomical landmark detection system for this anomaly detection problem. This system uses a landmark point distribution model (L-PDM) to find multiple landmark positions. The L-PDM is a statistical probabilistic model of all landmark positions in the human body, including five landmarks for each vertebra. Given a new volume, the proposed algorithm applies five hypotheses (normal, 11 or 13 thoracic vertebrae, 4 or 6 lumbar vertebrae) to the given spine and attempts to detect all the landmarks. Then, the most plausible hypothesis with the largest posterior likelihood is selected as the anatomy detection result. RESULTS: The proposed method was evaluated using 300 neck-to-pelvis CT datasets. For normal subjects, the vertebrae of 211/217 (97.2%) of the subjects were successfully determined as normal. For subjects with 23 or 25 vertebrae without a transitional vertebra (TV), the vertebrae of 9/10 (90%) of the subjects were successfully determined. For subjects with TV, the vertebrae of 71/73 (97.3%) of subjects were judged as partially successfully determined. CONCLUSION: Our algorithm successfully determined the number of vertebrae, and the feasibility of our proposed system was validated.

PURPOSE: A fully automatic multiatlas-based method for segmentation of the spine and pelvis in a torso CT volume is proposed. A novel landmark-guided diffeomorphic demons algorithm is used to register a given CT image to multiple atlas volumes. This algorithm can utilize both grayscale image information and given landmark coordinate information optimally. METHODS: The segmentation has four steps. Firstly, 170 bony landmarks are detected in the given volume. Using these landmark positions, an atlas selection procedure is performed to reduce the computational cost of the following registration. Then the chosen atlas volumes are registered to the given CT image. Finally, voxelwise label voting is performed to determine the final segmentation result. RESULTS: The proposed method was evaluated using 50 torso CT datasets as well as the public SpineWeb dataset. As a result, a mean distance error of [Formula: see text] and a mean Dice coefficient of [Formula: see text] were achieved for the whole spine and the pelvic bones, which are competitive with other state-of-the-art methods. CONCLUSION: From the experimental results, the usefulness of the proposed segmentation method was validated.

Rationale and Objectives: This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening. Materials and Methods: We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms. Results: The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001). Conclusions: The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP.

An automatic detection method for 197 anatomically defined landmarks in computed tomography (CT) volumes is presented. The proposed method can handle missed landmarks caused by detection failure, a limited imaging range and other problems using a novel combinatorial optimization framework with a two-stage sampling algorithm. After a list of candidates is generated by each landmark detector, the best combination of candidates is searched for by a combinatorial optimization algorithm using a landmark point distribution model (L-PDM) to provide prior knowledge. Optimization is performed by simulated annealing and iterative Gibbs sampling. Prior to each cycle of Gibbs sampling, another sampling algorithm is processed to estimate the spatial distribution of each target landmark, so that landmark positions without any correct detector-derived candidates can be estimated. The proposed method was evaluated using 104 CT volumes with various imaging ranges. The overall average detection distance error was 6.6mm, and 83.8, 93.2 and 96.5% of landmarks were detected within 10, 15 and 20mm from the ground truth, respectively. The proposed method worked even when most of the landmarks were outside of the imaging range. The identification accuracy of the vertebral centroid was also evaluated using public datasets and the proposed method could identify 70% of vertebrae including severely diseased ones. From these results, the feasibility of our framework in detecting multiple landmarks in various CT datasets was validated.

BACKGROUND AND PURPOSE: Experiences with computer-assisted detection of cerebral aneurysms in diagnosis by radiologists in real-life clinical environments have not been reported. The purpose of this study was to evaluate the usefulness of computer-assisted detection in a routine reading environment. MATERIALS AND METHODS: During 39 months in a routine clinical practice environment, 2701 MR angiograms were each read by 2 radiologists by using a computer-assisted detection system. Initial interpretation was independently made without using the detection system, followed by a possible alteration of diagnosis after referring to the lesion candidate output from the system. We used the final consensus of the 2 radiologists as the reference standard. The sensitivity and specificity of radiologists before and after seeing the lesion candidates were evaluated by aneurysm- and patient-based analyses. RESULTS: The use of the computer-assisted detection system increased the number of detected aneurysms by 9.3% (from 258 to 282). Aneurysm-based analysis revealed that the apparent sensitivity of the radiologists' diagnoses made without and with the detection system was 64% and 69%, respectively. The detection system presented 82% of the aneurysms. The detection system more frequently benefited radiologists than being detrimental. CONCLUSIONS: Routine integration of computer-assisted detection with MR angiography for cerebral aneurysms is feasible, and radiologists can detect a number of additional cerebral aneurysms by using the detection system without a substantial decrease in their specificity. The low confidence of radiologists in the system may limit its usefulness.

BACKGROUND: When the maximal diameter of an abdominal aortic aneurysm (AAA) exceeds a threshold, the likelihood of catastrophic rupture increases markedly. Therefore, surveillance at optimal intervals should be offered to patients with AAA. However, other than AAA diameter, there is no useful marker or index for predicting the expansion rate of an AAA or determining the optimal intervals for surveillance. The aim of this study was to evaluate the usefulness of calcium accumulation in the AAA for predicting its expansion rate. METHODS AND RESULTS: We performed a retrospective cohort study in 414 patients with infrarenal AAA who visited The University of Tokyo Hospital. The maximal diameter and extent of calcification of each AAA were evaluated by multidetector-row computed tomography imaging. There was an inverse correlation between the extent of calcification and the subsequent AAA expansion. A lower extent of calcification in the AAA as well as the AAA diameter and absence of coronary artery disease correlated with an accelerated expansion of the AAA. CONCLUSIONS: In AAA, a lower extent of calcification correlated with accelerated expansion. The calcification index of an AAA can be a useful predictor of its expansion rate. The study findings also support the theory that the mechanisms for progression in atherosclerosis with calcification and external expansion of an aneurysm are distinct.

CADの性能は機械学習によるところが大きく，開発用データセットと実運用時のデータの画質が異なる場合，通常は期待される性能が得られない．このため，使用施設のデータを継続的に収集して再学習を行うことでCADの性能改善が期待される．本論文では，遠隔読影環境での多施設連携によるCAD開発，実運用，および継続的性能改善について報告する．われわれが開発した統合的CAD実行／評価環境（CIRCUS CS）を遠隔読影環境へ導入するためにシステムの機能追加を行った．2011年9月より東大病院の初期開発用データセットで学習した2種類のCAD（肺結節検出，脳動脈瘤検出）を遠隔読影環境下で使用し，評価（フィードバック）データの収集を行った．収集したデータを用いた再学習のシミュレーションにより，施設ごとのCAD性能が改善されることを確認した．このことにより，画質の多様性に対応したCAD開発／臨床使用の促進が期待される．

OBJECTIVE: To develop automatic visceral fat volume calculation software for computed tomography (CT) volume data and to evaluate its feasibility. METHODS: A total of 24 sets of whole-body CT volume data and anthropometric measurements were obtained, with three sets for each of four BMI categories (under 20, 20 to 25, 25 to 30, and over 30) in both sexes. True visceral fat volumes were defined on the basis of manual segmentation of the whole-body CT volume data by an experienced radiologist. Software to automatically calculate visceral fat volumes was developed using a region segmentation technique based on morphological analysis with CT value threshold. Automatically calculated visceral fat volumes were evaluated in terms of the correlation coefficient with the true volumes and the error relative to the true volume. RESULTS: Automatic visceral fat volume calculation results of all 24 data sets were obtained successfully and the average calculation time was 252.7 seconds/case. The correlation coefficients between the true visceral fat volume and the automatically calculated visceral fat volume were over 0.999. CONCLUSIONS: The newly developed software is feasible for calculating visceral fat volumes in a reasonable time and was proved to have high accuracy.

解剖学的ランドマーク(Landmark:LM)の自動検出は、医用画像に含まれる解剖学的構造を認識する上で重要な情報をもたらす。我々はこれまで(1)局所アピアランスマッチングによるLM候補点(Landmark Candidate:LMC)の検出、(2)識別器アンサンブルを用いた誤検出LMCの削減、(3)LM間距離の事前知識を用いた事後確率最大化による最適なLMC組合せ選択の三つの処理からなるLM自動検出処理を提案してきた。各LMの多様性に対応するため、各LMの検出パラメータは実験的に選択していたが、本研究では、識別器アンサンブルの学習用サンプルに対する教師ラベル設定基準を新たにパラメータとし、更に検出処理の実験的最適化に新しい評価関数を導入することで、LM検出性能の改善を試みた。173種類のLMに対して30例のComputed Tomography(CT)像を用いて学習した検出処理について、20例のCT像を用いた検出性能評価実験を行ったところ、検出感度は98.8%、検出誤差距離は平均5.86±標準偏差6.78mmであった。この結果から、提案法の有用性を示すことができた。(著者抄録)

Segmentation of vertebral bones in computed tomographic data is important as a first stage of image-based radiological tasks. However, it is a challenging problem to segment an affected spine correctly In this study, we propose a new method of segmentation of thoracic and lumbar vertebral bodies from thin-slice computed tomographic images. Especially, we focus on a deformable model-based segmentation scheme to confirm the feasibility in clinical data sets with various bone diseases, such as bone metastases and scoliosis. As an application of this algorithm, virtual straightening of the thoracolumbar spine is also performed. Results on a database of 16 patients indicate the applicability of our method to spines affected by scoliosis and multiple bone metastases.

我々はこれまでに、曲率による候補領域抽出および表面情報を特徴量とした偽陽性(false positive,FP)削減処理を用いた肺結節の自動検出法を提案した。しかし、胸壁付着結節では、周辺構造の影響により表面情報の特徴量が孤立性結節の場合と異なる分布となるため、FP削減処理においてfalse negative(FN)となる。本論文では、肺野辺縁領域と内部領域でFP削減処理を別々に行う方法を提案する。提案方法では、抽出した候補領域に含まれる肺野辺縁領域のボクセル数の割合を計算し、候補領域群を肺野辺縁領域のサブセットあるいは内部領域のサブセットの2つに分類する。FP削減処理は分類されたサブセットごとに別々の識別器を用いて行う。性能評価の結果、識別器を追加することでFP削減性能を向上できることが確認できた。(著者抄録)

We investigated the characteristics and utility of gadobenate dimeglumine (Gd-BOPTA) for MRI of the mouse liver. Mice were imaged under isoflurane anesthesia using a T-1-weighted, three-dimensional fast low-angle shot (3D FLASH) sequence before and after intravenous or subcutaneous injection of Gd-BOPTA, and the time course of the contrast effect was examined. The appropriate dose for subcutaneous injection was determined visually, and the inter- and intra-observer reproducibilities in liver volumetry were evaluated with and without contrast injection. When mice were imaged sequentially before and after Gd-BOPTA injection and isoflurane anesthesia was maintained throughout the experiment, a long-lasting contrast effect was noted in the liver. Subcutaneous injection caused delayed, but favorable, enhancement. Washout from the liver was definitely accelerated in conscious mice in comparison with anesthetized mice. Visual evaluation indicated that a dose of 0.1 mmol/kg was appropriate for clear delineation of the entire liver margin, and the application of Gd-BOPTA significantly improved the inter- and intra-observer reproducibilities of liver volumetry. In conclusion, the intravenous or subcutaneous injection of Gd-BOPTA has a favorable contrast effect for the mouse liver, resulting in clear visualization of the liver border and improved reproducibility of liver volumetry. The possible influence of anesthesia on the pharmacokinetics of a contrast agent should be considered in determining the optimal scan timing. Copyright (c) 2007 John Wiley & Sons, Ltd.

本論文では、胸部CTにおける曲率を用いた肺結節検出方法で発生する血管分岐の中心部の偽陽性を削減する方法として、結節および血管の表面情報を利用した偽陽性削減法を提案する。提案システムではまず、3次元曲率による曲面の形状指標であるshape indexを用いた閾値処理ならびに領域拡張により候補領域を抽出する。なお、さまざまな大きさの結節に対応するために、ヘッセ行列の固有値解析によるスケールマッチングを併用する。そして、結節および血管の表面領域を抽出し、得られた特徴量により候補領域から偽陽性の削減を行う。2名の読影医により長径が3mm以上の肺結節が存在すると診断された16症例に対して性能評価を行った。その結果、提案する偽陽性削減法を用いることにより血管分岐の中心部に存在する偽陽性を良好に削減できることが確認できた。(著者抄録)

Objective. We evaluated disease progression in a mouse model of a hematologic malignancy using a multimodality approach that included bioluminescence imaging (BLI) and magnetic resonance imaging (MRI). We aimed to examine the feasibility and capability of BLI and MRI and to establish techniques for quantitative assessment of disease severity. Methods. Mice were inoculated intravenously with Ba/F3 cells transduced with firefly luciferase and p190 BCR-ABL genes. Disease progression in a given mouse was observed longitudinally by in vivo BLI and MRI (n = 5). Imaging studies, including in vivo BLI and MRI of living mice and ex vivo BLI of excised organs, were also performed at various time points (n = 4, 3, 4, and 4 at 1, 2, 3, and 4 weeks after cell inoculation). Results. Longitudinal studies allowed the assessment of disease progression for each mouse, and an approximately 4-log increase in whole-body BLI signal was shown after initial detection. MRI demonstrated progressive hepatosplenomegaly and growth of hepatic nodules. Ex vivo BLI demonstrated proliferation of the implanted cells in various organs including bone marrow, and the signal for each organ increased with time (Spearman's rank correlation coefficient, R = 0.831-0.914) and as the whole-body signal, observed by in vivo BLI, increased (R = 0.921-0.982). MRI measurements of liver and spleen volumes were shown to have excellent accuracy and volume increases significantly correlated with the BLI organ signal (liver, R = 0.875; spleen, R = 0.971). Conclusion. BLI and MRI allow repeated assessment of disease progression in a mouse model of a hematologic malignancy and provide quantitative markers of disease severity. BLI and MRI measurements reveal different details of disease progression and may play complementary roles in comprehensive assessment.(c) 2007 International Society for Experimental Hematology. Published by Elsevier Inc.

The aims of this study were to investigate the applicability of Fourier fitting in the magnetic resonance (MR) evaluation of left ventricular (LV) function and to determine the optimal number of harmonies for fitting. Cine cardiac MR imaging was performed in 10 subjects, and an LV time-volume curve was generated. Fourier fitting was applied to the original curve using 1-10 harmonies, and the qualities of the time-volume curve and first-derivative curve were evaluated. LV functional parameters were calculated from curves generated with and without fitting. The quality of the original time-volume curve was good, and Fourier fitting had no substantial effect on functional parameters obtained directly from the time-volume curve such as ejection fraction. The first-derivative curve generated without fitting showed substantial artificial fluctuation. The application of Fourier fitting depressed the fluctuation and tended to decrease estimates of peak ejection rate and peak filling rate. Five or six harmonies appeared to be appropriate for obtaining a high-quality first-derivative curve. In conclusion, Fourier fitting was indicated to aid in reducing the artificial fluctuation of the first-derivative curve generated from cine cardiac MR imaging and to contribute to the evaluation of functional parameters derived from the first-derivative curve. (c) 2006 Elsevier Inc. All rights reserved.

PURPOSE: To determine the feasibility of imaging living mice with a 1-T compact MRI system and investigate appropriate imaging techniques for use in routine animal experiments. MATERIALS AND METHODS: An MRI system consisting of a 1-T permanent magnet and compact console was used. Images of the entire trunks of living mice were obtained on the system using a T1-weighted three-dimensional fast low-angle shot (3D FLASH) sequence, and image quality was evaluated in relation to imaging techniques. RESULTS: Restraint of respiratory motion improved the image quality. Decreasing the slice thickness reduced artificial inhomogeneity in signal intensity (SI). Substantial effects of TR and FA on image quality were also demonstrated. With the determined techniques, images covering the entire trunk with a voxel size of 0.26x0.26x0.52 mm were acquired in an acquisition time of five minutes 28 seconds and a total experiment time of <20 minutes, and various organs and subcutaneous tumors were clearly visualized. CONCLUSION: The compact MRI system provides images of living mice with acceptable quality in a reasonable time. Considering its convenience, it appears to be suitable for use in routine mouse experiments.

本論文では,モフォロジー処理を用いたスペクトルサブトラクションにおけるミュージカルノイズ除去方法を提案する.提案方法では,スペクトログラム上でミュージカルノイズが孤立点として現れることに注目し,モフォロジー処理が孤立点除去に向いていることを利用してミュージカルノイズの除去を行う.また,提案方法ではミュージカルノイズ検出の際のしきい値を必要とせず,かつモフォロジー処理は比較演算のみで行える.そのため,提案方法は従来方法と比較してシステムの設計が容易で,かつ少ない計算回数でミュージカルノイズの除去が行える.提案方法についてNOISEX-92の4種類の雑音による性能評価を行う.その結果,提案方法は従来方法に比べて少ない計算回数で音声強調を行うことができ,かつミュージカルノイズ除去性能が優れていることを示す.

The aim of this study was to investigate the effect of temporal resolution on the estimation of left ventricular (LV) function by cardiac magnetic resonance (MR) imaging using a steady-state free precession (SSFP) sequence. Left ventricular function was assessed by cine MR imaging using a segmented SSFP sequence in 10 healthy volunteers. Views per segment (VPS) were set at 8 and 20, resulting in high and low true temporal resolution, respectively. Irrespective of VPS, images were reconstructed at 40 cardiac phases, providing high apparent temporal resolution. Data were analyzed using 40, 20 and 10 phases to simulate different apparent temporal resolutions. Increasing the cardiac phases used for analysis slightly decreased mean end-systolic volume (ESV) and slightly increased mean ejection fraction (EF). No substantial difference in estimates of end-diastolic volume (EDV) was found between VPSs of 8 and 20. Imaging with a VPS of 20 yielded a larger ESV and smaller EF than imaging with a VPS of 8 when 40 phases were used. In conclusion, low true temporal resolution causes overestimation of ESV and underestimation of EF. Improvement of apparent temporal resolution mildly reduces but does not eliminate the errors caused by low true temporal resolution. (c) 2005 Elsevier Inc. All rights reserved.

音声強調において, 音声領域と雑音領域の判別は音声の雑音除去と明瞭性の向上の両面から重要である。本論文では, 雑音量に依存しない音声領域と雑音領域の判別方法を利用した音声強調法を提案する。提案方法では, 音声領域と雑音領域の判別のしきい値を雑音量によって適応的に変化させることにより, 判別時の雑音の影響を低減させる。提案方法についてNOISEX-92の4種類の雑音による性能評価を行う。その結果, 提案方法は従来方法より音声/雑音領域の判別が雑音量に依存せず, 正確に行われることを示す。提案方法によって強調した音声は雑音除去性能を維持しながら音声歪を減少できることを示す。

This paper presents a speech enhancement using the classification between the dominants of speech and noise. In our system, a new classification scheme between the dominants of speech and noise is proposed. The proposed classifications use the standard deviation of the spectrum of observation signal in each band. We introduce two oversubtraction factors for the dominants of speech and noise, respectively. And spectral subtraction is carried out after the classification. The proposed method is tested on several noise types from the Noisex-92 database. From the investigation of segmental SNR, Itakura-Saito distance measure, inspection of spectrograms and listening tests, the proposed system is shown to be effective to reduce background noise. Moreover, the enhanced speech using our system generates less musical noise and distortion than that of conventional systems.

Kinetic MRI images has been developed and often applied to the diagnosis of soft tissues. The diagnosis of the temporomandibular joint seemed to be one of the typical application fields and has been already clinically performed in some hospitals. Kinetic MRI images cannot be dealt with by DICOM systems, since the information elements and transfer syntax has not been defined yet. We tried to define them and examined its performances. Several objects of temporomandibular joint kinetic MRI images in Quick TIME format were created using the newly defined information elements. The objects were transferred and stored to a DICOM image server using CTN software. The stored images were successfully reconstructed and replayed. The outline of the newly defined information elements, the procedures for making and reconstruction of the objects were discussed in this paper.

近年, DICOM(Digital Imaging and Communications in Medicine)対応の医用画像機器が増えており, 画像データがDICOM形式で提供される機会が多くなった。そこで我々は, 東京都立保健科学大学内に教育・研究用DICOMネットワークを構築した。CPU室内のUNIXサーバ上でCTN(Central Test Node)を使用したDICOM画像サーバを構築した。また, 放射線学科助手室内のWindowsNTマシン2台でDICOM Storage Media製作用サーバ群を構築した。さらに, クライアントを数台用意し, サーバの画像を観察することを可能にした。ネットワーク構築後の各種検証の結果は良好であり, 教育・研究用のDICOMネットワークとして大学内のニーズに応えられると思われる。