研究者詳細 - 神谷　亨

論文 - 神谷　亨

分割表示751 件中 361 - 380 件目／全件表示 >>

Detection of Abnormal Candidate Regions on Temporal Subtraction Images Based on DCNN 査読有り

Nagao, Miyake, Yoshino, Lu, Tan, Kim, Murakami, Aoki, Hirano, Kido

Proceedings of the 17th International Conference on Control, Automation and Systems 1444 - 1448 2017年10月

Environment Recognition for Navigation of Autonomous Wheelchair from a Video Image 査読有り

Nakayama, Lu, Tan, Kim

Proceedings of the 17th International Conference on Control, Automation and Systems 1439 - 1443 2017年10月

Automatic classification of lung nodules on MDCT images with the temporal subtraction technique 査読有り

Yoshino Y., Miyajima T., Lu H., Tan J., Kim H., Murakami S., Aoki T., Tachibana R., Hirano Y., Kido S.

International Journal of Computer Assisted Radiology and Surgery 12 ( 10 ) 1789 - 1798 2017年10月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

© 2017, CARS. Purpose: A temporal subtraction (TS) image is obtained by subtracting a previous image, which is warped to match the structures of the previous image and the related current image. The TS technique removes normal structures and enhances interval changes such as new lesions and substitutes in existing abnormalities from a medical image. However, many artifacts remaining on the TS image can be detected as false positives. Method: This paper presents a novel automatic segmentation of lung nodules using the Watershed method, multiscale gradient vector flow snakes and a detection method using the extracted features and classifiers for small lung nodules (20 mm or less). Result: Using the proposed method, we conduct an experiment on 30 thoracic multiple-detector computed tomography cases including 31 small lung nodules. Conclusion: The experimental results indicate the efficiency of our segmentation method.

DOI： 10.1007/s11548-017-1598-1

Scopus

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Image Registration Techniques and Its Application for Computer Aided Dianosis in Medical Field 招待有り査読有り

Kim

2nd Ingernational Conference on Biomedical Signal and Image Processing 2017年08月

Statistical Shape Model Generation Using Diffeomorphic Surface Registration 査読有り

J. Wu, G. Li, H. Lu, Kim, P.O. Ogubona

Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing 37 - 41 2017年08月

Automatic Identification of Circulating Tumor Cells in Fluorescence Microscopy Images Based on ANN 査読有り

Tsuji, Lu, Tan, Kim, Yoneda, Tanaka

Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing 1 - 6 2017年08月

An Interactive Technique of Fast Vertebral Segmentation for Computed Tomography Images with Bone Metastasis 査読有り

Dong, Lu, Kim, Aoki, Yihong Zhao, Zhao

Proceedings of the 2nd International Conference on Biomedical Signal and Image Processing 29 - 36 2017年08月

An interactive technique of fast vertebral segmentation for computed tomography images with bone metastasis 査読有り国際誌

Dong R., Lu H., Kim H., Aoki T., Zhao Y., Zhao Y.

ACM International Conference Proceeding Series 29 - 36 2017年08月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2017 Association for Computing Machinery. Computer-aided diagnosis (CAD) system can assistant radiologists to diagnose bone metastasis, which not only reduces burden on workload but also improves diagnostic accuracy. As key step in CAD system, vertebral segmentation can directly affect diagnostic results. In order to obtain high accurate segmentation results, we propose a connected component Labeled Graph Cuts (LGC) algorithm. The proposed method is tested on 100 computed tomography (CT) slices. The assessed quantitatively of experimental results is compared with those by radiologist. The proposed method has a 96.72[%] of True Positive Rate (TPR), and 1.84[%] of False Positive Rate (FPR), which have better performance than conventional Graph Cuts algorithm, 90.07[%] of TPR and 2.32[%] of FPR.

DOI： 10.1145/3133793.3133795

Scopus

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Statistical shape model generation using diffeomorphic surface registration 査読有り国際誌

Wu J., Li G., Lu H., Kim H., Ogunbona P.

ACM International Conference Proceeding Series 37 - 41 2017年08月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2017 Association for Computing Machinery. Statistical shape modelling is an efficient and robust method for medical image segmentation in computer-aided diagnosis. The key step in building a statistical shape model is to find corresponding landmarks in each instance of a training set. In this paper, a novel landmark correspondence estimation method that uses edge collapse surface simplification and the sphere registration is proposed. All the landmarks are selected and transformed by spherical conformal mapping from the instances of the training set and the associated correspondence are automatically found on the spheres. We applied our method on 21 cases of 3-D right lung shapes. The results of image segmentation experiment indicate that our method has a positive influence on the accuracy of segmentation result.

DOI： 10.1145/3133793.3133796

Scopus

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Automatic identification of circulating tumor cells in fluorescence microscopy images based on ANN 査読有り国際誌

Tsuji K., Lu H., Tan J., Kim H., Yoneda K., Tanaka F.

ACM International Conference Proceeding Series 1 - 6 2017年08月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2017 Association for Computing Machinery. Circulating tumor cells (CTCs) are a useful biomarker since they may have some information about cancer metastasis. The blood from cancer patient is analyzed by a fluorescence microscope. It takes a large number of photos for each case, and many cells are contained in the microscopy images. Thus, analyzing them is hard work for pathologists. This work tends to depend on the individual skill of pathologist so misdiagnosis may be happen. In this paper, we develop an automatic CTCs identification method in fluorescence microscopy images based on artificial neural network. We applied our proposed method to 5040 microscopy images (6 cases), and evaluated the effectiveness of our method by using leave-one-out cross validation. We achieve a true positive rate of 98.65 [%] and a false positive rate of 18.24 [%].

DOI： 10.1145/3133793.3133798

Scopus

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画像処理技術による診断支援への応用

金

全国歯科大学・歯学部付属病院診療放射線技師連絡協議会会誌 2017年07月

Moving objects detection employing iterative update of the background 査読有り国際誌

Setyawan F., Tan J., Kim H., Ishikawa S.

Artificial Life and Robotics 22 ( 2 ) 168 - 174 2017年06月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2017, ISAROB.Detection of objects from a video is one of the basic issues in computer vision study. It is obvious that moving objects detection is particularly important, since they are those to which one should pay attention in walking, running, or driving a car. This paper proposes a method of detecting moving objects from a video as foreground objects by inferring backgrounds frame by frame. The proposed method can cope with various changes of a scene including large dynamical change of a scene in a video taken by a stationary/moving camera. Experimental results show satisfactory performance of the proposed method.

DOI： 10.1007/s10015-016-0347-9

Scopus

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Activity representation by SURF-based templates 査読有り

Md. Atiqur Rahman Ahad, JK Tan, H Kim, S Ishikawa

Computer Methods in Biamechanics and Biomedical Engineering: Image & Visualization 1 - 11 2017年04月

A supervised correspondence method for statistical shape model building 査読有り

Li G., Honda H., Yoshino Y., Kim H., Xiao Z.

2016 IEEE International Conference on Signal and Image Processing, ICSIP 2016 37 - 40 2017年03月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2016 IEEE.The construction of statistical shape model (SSM) is an important research topic in medical imaging benefited from its robust and nature represent of anatomical structures. Place-march of corresponding landmarks is one of the major factors influencing 3D SSM quality. In this paper, we present a supervised correspondence method for fast building SSM, which includes two main steps, i.e., surface data alignment and landmarks specified based on surface parameterization. The framework is validated with statistical models of the liver constructed from contrast CT images. The experiment results demonstrate that the generated model is statistical and anatomically meaningful.

DOI： 10.1109/SIPROCESS.2016.7888219

Scopus

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An ego-camera based finger-spelling recognition system 査読有り国際誌

Tan J., Hamada S., Hirakawa M., Kim H., Ishikawa S.

IEEE Region 10 Annual International Conference, Proceedings/TENCON 358 - 363 2017年02月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2016 IEEE.This paper describes a portable system for finger-spelling recognition, employing a PC and a video taken by an ego-camera mounted on the body of a person who does finger-spelling. The system is intended to be a useful tool for an orally impaired person to communicate to anyone at any place by carrying it with him/her. The images of the finger-spelling hand of a user who is carrying the system is captured by an ego-camera. The hand is extracted from arbitrary backgrounds by use of a Gaussian mixture model and skin color evaluation: The trimmed and normalized image of the extracted hand is recognized employing the feature space defined by applying the principal component analysis to the learning data containing 45 finger-spelled Japanese Hiragana letters each with 50 samples and the nearest neighbor method. The on-line performance of the proposed system is experimentally shown.

DOI： 10.1109/TENCON.2016.7848021

Scopus

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経時的差分像技術を用いた結節状候補陰影の検出

金，村上，寺澤，青木，木戸

呼吸機能イメージング研究会学術集会講演論文集 58 - 58 2017年01月

Underwater image super-resolution by descattering and fusion 査読有り国際誌

Lu H., Li Y., Nakashima S., Kim H., Serikawa S.

IEEE Access 5 670 - 679 2017年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2013 IEEE. Underwater images are degraded due to scatters and absorption, resulting in low contrast and color distortion. In this paper, a novel self-similarity-based method for descattering and super resolution (SR) of underwater images is proposed. The traditional approach of preprocessing the image using a descattering algorithm, followed by application of an SR method, has the limitation that most of the high-frequency information is lost during descattering. Consequently, we propose a novel high turbidity underwater image SR algorithm. We first obtain a high resolution (HR) image of scattered and descattered images by using a self-similarity-based SR algorithm. Next, we apply a convex fusion rule for recovering the final HR image. The super-resolved images have a reasonable noise level after descattering and demonstrate visually more pleasing results than conventional approaches. Furthermore, numerical metrics demonstrate that the proposed algorithm shows a consistent improvement and that edges are significantly enhanced.

DOI： 10.1109/ACCESS.2017.2648845

Scopus

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Highly accurate energy-conserving flexible touch sensors 査読有り国際誌

Lu H., Li Y., Li Y., Serikawa S., Kim H.

Sensors and Materials 29 ( 6 ) 611 - 617 2017年01月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

© MYU K.K. Smart touch sensors are used in many applications, such as the iPhone and some smart home systems. Recent touch sensors perform well in consumer electrical devices; however, there are some drawbacks. For example, most touch sensors have low accuracy for detecting human movements. Many require significant power and have a fixed shape. We propose a flexible, highly accurate, and energy-conserving touch sensor. Our primary contributions are as follows: (1) an energy-conserving touch sensor is developed and tested experimentally; (2) a flexible and arbitrarily shaped touch sensor is designed; and (3) the manufacturing cost is very low and up to 200 touch sensors can be connected to the system. As a result, this energy-conserving touch sensor can be fabricated using common manufacturing processes for consumer electronic devices.

DOI： 10.18494/SAM.2017.1458

Scopus

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Depth Map Reconstruction for Underwater Kinect Camera Using Inpainting and Local Image Mode Filtering 査読有り国際誌

Lu H., Zhang Y., Li Y., Zhou Q., Tadoh R., Uemura T., Kim H., Serikawa S.

IEEE Access 5 7115 - 7122 2017年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2017 IEEE. Underwater optical cameras are widely used for security monitoring in ocean, such as earthquake prediction and tsunami alarming. Optical cameras recognize objects for autonomous underwater vehicles and provide security protection for sea-floor networks. However, there are many issues for underwater optical imaging, such as forward and backward scattering, light absorption, and sea snow. Many underwater image processing techniques have been proposed to overcome these issues. Among these techniques, the depth map gives important information for many applications of the post-processing. In this paper, we propose a Kinect-based underwater depth map estimation method that uses a captured coarse depth map by Kinect with the loss of depth information. To overcome the drawbacks of low accuracy of coarse depth maps, we propose a corresponding reconstruction architecture that uses the underwater dual channels prior dehazing model, weighted enhanced image mode filtering, and inpainting. Our proposed method considers the influence of mud sediments in water and performs better than the traditional methods. The experimental results demonstrated that, after inpainting, dehazing, and interpolation, our proposed method can create high-accuracy depth maps.

DOI： 10.1109/ACCESS.2017.2690455

Scopus

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細胞領域の論理積を用いた蛍光顕微鏡画像からの血中循環がん細胞の自動検出査読有り

辻幸喜, 陸慧敏, タンジュークイ, 金亨燮, 米田和恵, 田中文啓

医用画像情報学会雑誌 ( 医用画像情報学会 ) 34 ( 4 ) 151 - 155 2017年01月

担当区分：責任著者記述言語：日本語掲載種別：研究論文（学術雑誌）

<p>Circulating tumor cells（CTCs）can be a useful biomarker. They may have some information about the malignant disease, since they are one of causes of the cancer metastasis. The blood sample from cancer patient is analyzed by fluorescence microscope. This microscope takes enlarged images with three types of lights（red, green and blue）,and specific materials are reacted respectively. The blood contains a lot of cells, but there are few CTCs. Therefore analyzing them is not easy work for pathologists. In this study, we develop a method which detects circulating tumor cells in fluorescence microscopy images automatically. Our proposed method has three steps. First, we extract cell regions in microscopy images by using filtering processing. Second, we separate the connecting cell regions into single cell regions,based on the branch and bound algorithm. Finally, we identify CTCs by using logical conjunction method. We demonstrated the effectiveness of our proposed method using 6 cases（5040 microscopy images）, and we evaluated the performance of CTCs identification. Our proposed method achieved, a true positive rate of 95.27 [%] and a false positive rate of 6.172 [%] respectively. And we confirmed the effectiveness of the logical conjinction for CTCs identicication.</p>

DOI： 10.11318/mii.34.151

CiNii Article

CiNii Research

その他リンク： https://ci.nii.ac.jp/naid/130006267703

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