研究者詳細 - 神谷　亨

論文 - 神谷　亨

分割表示757 件中 361 - 380 件目／全件表示 >>

Extraction of Spinal Candidate Region from A Dental MR Imaging 査読有り

Suetani, Lu, Tan, Kim, Tanaka, Kitou, Morimoto

Proceedings of the 17th International Conference on Control, Automation and Systems 1601 - 1604 2017年10月

Image Registration of Vertebral Region from CT Images Based on Salient Region Feature 査読有り

Sato, Lu, Tan, Kim, Murakami, Ueno, Terasawa, Aoki

Proceedings of the 17th International Conference on Control, Automation and Systems 1597 - 1600 2017年10月

Classification of Osteoporosis from Phalanges CR Images Based on DCNN 査読有り

Hatano, Murakami, Lu, Tan, Kim, Aoki

Proceedings of the 17th International Conference on Control, Automation and Systems 1593 - 1596 2017年10月

Automatic Liver Segmentation from Multiphase CT images by Using Level Set Method 査読有り

Saito, Lu, Tan, Kim, Yamamoto, Kido, Tanabe

Proceedings of the 17th International Conference on Control, Automation and Systems 1590 - 1592 2017年10月

Image Analysis of Cleft Lip from Moire Image Based on Symmetry Analysis 査読有り

Yamada, Lu, Tan, Kim, Kimura, Okawachi, Nozoe, Nakamura

Proceedings of the 17th International Conference on Control, Automation and Systems 1586 - 1589 2017年10月

Detection of Lung Nodules on Temporal Subtraction Images Using 3D Sparse Coding 査読有り

Tanaka, Miyake, Lu, Tan, Kim, Murakami, Aoki, Hirano, Kido

Proceedings of the 17th International Conference on Control, Automation and Systems 1455 - 1457 2017年10月

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

Tsuji, Lu, Tan, Kim, Yoneda, Tanaka

Proceedings of the 17th International Conference on Control, Automation and Systems 1449 - 1454 2017年10月

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

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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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

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

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

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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