研究者詳細 - 丹上　結乃純

論文 - 丹上　結乃純

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Automatic detection of GGO regions on CT images in LIDC dataset based on statistical features 査読有り

Yokota K., Maeda S., Kim H., Tan J., Ishikawa S., Tachibana R., Hirano Y., Kido S.

2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 1374 - 1377 2014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）

© 2014 IEEE. Detection of pulmonary nodules with ground glass opacity (GGO) is a difficult task in radiology. Follow up is often required in medical fields. But diagnosis based on CT images are dependent on ability and experience of radiologists. In addition to that, enormous number of images increase their burden. So, to improve the detection accuracy and to reduce the burden of doctors, a CAD (Computer Aided Diagnosis) system is expected. So, in this paper, we propose an automatic algorithm for GGO detection on CT images. At first, vessel areas are removed from original CT images by using 3D Line Filter and then candidate regions are detected by threshold processing. After that, we calculate statistical features of segmented candidate regions and use artificial neural network (ANN) to distinguish final candidate regions. We applied the proposed method to 31 CT image sets in the Lung Image Database Consortium (LIDC) which is supplied by National Center Institute (NCI). In this paper, we show the experimental results and give discussions.

DOI： 10.1109/SCIS-ISIS.2014.7044692

Scopus

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Automatic identification of lung candidate nodules on chest CT images based on temporal subtraction images 査読有り

Tanaka S., Ikeda Y., Kim H., Tan J., Ishikawa S., Murakami S., Aoki T., Tachibana R., Hirano Y., Kido S.

2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 1364 - 1368 2014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）

© 2014 IEEE. Lung cancer is the most common cause of death from cancer worldwide. Therefore, for the purpose of early detection of cancer, mass screening and thorough examination have been carried out. Lung cancer is detected easily by using chest MDCT (Multi Detector-row Computed Tomography) images. However, radiologists are apprehended burden by many chest MDCT images which are required interpretation of radiograms. So the CAD (Computer Aided Diagnosis) systems that could relieve radiologist's stress and diagnose accuracy could be improved are expected. One of the CAD systems, temporal subtraction technique that emphasized time-dependent change is reported. This technique is used for diagnosis assistance of detected candidate nodules from CT images. In this paper, the candidate nodules under 20[mm] are extracted from temporal subtraction images. We highlighted the candidate nodules based on features analysis of images. We applied proposed method to 31 cases of chest MDCT images in which the number of nodules was more than one. We got a result of TPR:96.9[%], FPR:6.45[/case].

DOI： 10.1109/SCIS-ISIS.2014.7044780

Scopus

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Detection of a bicycle in video images using MSC-HOG feature 査読有り

Jung H., Ehara Y., Tan J., Kim H., Ishikawa S.

International Journal of Innovative Computing, Information and Control 10 ( 2 ) 521 - 533 2014年02月

記述言語：英語掲載種別：研究論文（学術雑誌）

Traffic accidents are decreasing due to the influence of technology advancement; however accidents still occur due to carelessness of drivers. Therefore, many researchers have been studying how to realize an advanced safety system. The Histograms of Oriented Gradients (HOG) feature is well known as a useful method of detecting a standing human in various kinds of backgrounds. Unlike a person, a bicycle can appear differently from various angles. In this paper, we propose a method of detecting a bicycle on the road using improved HOG feature named MSC-HOG feature and the Real-AdaBoost algorithm. Experimental results and evaluation show satisfactory performance of the proposed method. © 2014 ISSN 1349-4198.

Scopus

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Automatic segmentation of phalanges regions on CR images based on MSGVF Snakes 査読有り

Kajihara S., Murakami S., Kim H., Tan J., Ishikawa S.

International Conference on Control, Automation and Systems 1290 - 1293 2014年01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）

© 2014 Institute of Control, Robotics and Systems (ICROS). Rheumatoid arthritis and osteoporosis are two common orthopedic diseases. Rheumatoid arthritis is a disease that inflammation occurs in the joint, which always causes the joints are able to move freely. Osteoporosis is a disease that bone mineral content is reduced and risk of fragility fracture increases. As one of the diagnostic methods, medical imaging by photographed CR equipment has been widely accepted. However, some problems such as mass screening data sets and mis-diagnosis are still remained in visual screening. In order to solve these problems and reduce the burden to physicians, needs of an automatic diagnosis system capable of performing quantitative analysis is anticipated. In this paper, we carry out the development of a segmentation method of phalanges regions from CR images of the hand to perform a quantitative evaluation of rheumatoid arthritis and osteoporosis. The proposed method is carried out crude segmentation of phalanges regions from CR images of the hand, and extracts the detailed phalanges regions by Multi Scale Gradient Vector Flow Snakes (MSGVF) method. In our study, we performed Snakes algorithm to give an initial control points on MSGVF algorithm. We applied our method on three pairs of CR temporal images of phalanges regions, which are called as the previous images and the current images. We got the segmentation results of 5.95 [%] of false-positive rate and 92.9 [%] of true-positive rate.

DOI： 10.1109/ICCAS.2014.6987755

Scopus

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Recognizing a road environment using multiple-window bag of features 査読有り

Morita, S., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings of International Conference on Artificial Life & Robotics (ICAROB2014) GS5-1,1 - GS5-1,4 CD-Rom: 4 Pages 2014年01月

Fast motion detection in a dynamic background 査読有り

Mudjirahardjo, P., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings of International Symposium on Artificial Life and Robotics 896 - 900 2014年01月

A method of detecting a bicycle using circles 査読有り

Jung, H., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings of International Symposium on Artificial Life and Robotics 365 - 368 2014年01月

Visualizing scaler stroke motion by a camera-computer system 査読有り

Kuroiwa, M., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings of International Symposium on Artificial Life and Robotics 196 - 199 2014年01月

Comparison of feature detectors for obstacles detection 査読有り

Qian, S., Tan, J. K., Kim, H. S., Ishikawa, S., Morie, T., Shinomiya, T.

Proceedings of International Conference on Artificial Life & Robotics (ICAROB2014) GS5-5,1 - GS5-5,4 CD-Rom: 4 Pages 2014年01月

ブースティングによる機械学習に基づく海底物体の検出査読有り

丹康弘，タンジュークイ，金亨燮，石川聖二

日本船舶海洋工学会論文集 18 115 - 121 2013年12月

A novel pedestrian detector on low-resolution images: Gradient LBP using patterns of oriented edges 査読有り

Boudissa, A., Tan, J.K., Kim, H., Shinomiya, T., Ishikawa, S.

IEICE Transactions on Information & Systems E96-D ( 12 ) 2882 - 2887 2013年12月

Recognizing human actions using histogram of local binary patterns 査読有り

Sk, Md. M. Ahsan, J.K. Tan, H. Kim, S. Ishikawa

Proceedings 2013 IEEE/SICE Int. Sympo. on System Integration (SII2013) 54 - 59 2013年12月

Automatic classification of the seabed sediments based on HLAC 査読有り

Tan, Y., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings 2013 IEEE/SICE Int. Sympo. on System Integration (SII2013) 653 - 658 2013年12月

3-D recovery of a non-rigid object from a single camera view employing multiple coordinates representation 査読有り

Ishikawa, Sh., Tan, J.K., Kim, H., Ishikawa, S.

Proceedings 2013 2nd IAPR Asian Conf. on Pattern Recognition: Recent Advances in Computer Vision and Pattern Recognition (RACVPR) 946 - 950 2013年11月

Semantic characteristics prediction of pulmonary nodule using Artificial Neural Networks 査読有り

Li G., Kim H., Tan J., Ishikawa S., Hirano Y., Kido S., Tachibana R.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 5465 - 5468 2013年10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）

Since it is difficult to choose which computer calculated features are effective to predict the malignancy of pulmonary nodules, in this study, we add a semantic-level of Artificial Neural Networks (ANNs) structure to improve intuition of features selection. The works of this study include two: 1) seeking the relationships between computer-calculated features and medical semantic concepts which could be understood by human; 2) providing an objective assessment method to predict the malignancy from semantic characteristics. We used 60 thoracic CT scans collected from the Lung Image Database Consortium (LIDC) database, in which the suspicious lesions had been delineated and annotated by 4 radiologists independently. Corresponding to the two works of this study, correlation analysis experiment and agreement experiment were performed separately © 2013 IEEE.

DOI： 10.1109/EMBC.2013.6610786

Scopus

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Road region estimation and obstacles extraction using a monocular camera 査読有り

Qian, S., Tan, J.K., Kim, H., Ishikawa, S., Morie, T., Shinomiya, T.

International Journal of Innovative Computing, Information and Control 9 ( 9 ) 3561 - 3572 2013年09月

Abnormal motion detection in an occlusion environment 査読有り

Mudjirahardjo, P., Tan, J. K., Kim, H. S., Ishikawa, S.

Proceedings of SICE Annual Conference 2013 1398 - 1402 2013年09月