KAMIYA Toru

写真a

Title

Professor

Laboratory

1-1 Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka

Research Fields, Keywords

Image measurement, Medical imaging

E-mail

E-mail address

Phone

+81-93-884-3185

Fax

+81-93-861-1159

Undergraduate Education 【 display / non-display

  • 1994.03   Kyushu Institute of Technology   Faculty of Engineering   Graduated   JAPAN

Degree 【 display / non-display

  • Kyushu Institute of Technology -  Doctor of Engineering  2001.03

Biography in Kyutech 【 display / non-display

  • 2011.04
    -
    Now

    Kyushu Institute of TechnologyFaculty of Engineering   Department of Mechanical and Control Engineering   Professor  

 

Publications (Article) 【 display / non-display

  • Hyperspectral Images Segmentation Using Active Contour Model for Underwater Mineral Detection

      810   513 - 522   2020.01  [Refereed]

     View Summary

    © 2020, Springer Nature Switzerland AG. In this paper, we design a novel underwater hyperspectral imaging technique for deep-sea mining detection. The spectral sensitivity peaks are in the region of the visible spectrum, 580, 650, 720, 800 nm. In addition, to the underwater objects recognition, because of the physical properties of the medium, the captured images are distorted seriously by scattering, absorption and noise effect. Scattering is caused by large suspended particles, such as in turbid water, which contains abundant particles, algae, and dissolved organic compounds. In order to resolve these problems of recognizing mineral accurately, fast and effectively, an identifying and classifying algorithm is proposed in this paper. We take the following steps: firstly, through image preprocessing, hyperspectral images are gained by using denoising, smoothness, image erosion. After that, we segment the cells by the method of the modified active contour method. These methods are designed for real-time execution on limited-memory platforms, and are suitable for detecting underwater objects in practice. The Initial results are presented and experiments demonstrate the effectiveness of the proposed imaging system.

    DOI Scopus

  • DeepEye: A Dedicated Camera for Deep-Sea Tripod Observation Systems

      810   507 - 511   2020.01  [Refereed]

     View Summary

    © 2020, Springer Nature Switzerland AG. The deep-sea tripod systems are designed and built at the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center (PCMSC) in Santa Cruz, California. They are recovered in late September 2014 after spending about half a year collecting data on the floor of the South China Sea. The deep-sea tripod systems are named as Free-Ascending Tripod (FAT), are deployed at 2,100 m water depth—roughly 10 times as deep as most tripods dedicated to measuring currents and sediment movement at the seafloor. Deployment at this unusual depth was made possible by the tripod’s ability to rise by itself to the surface rather than being pulled up by a line. Instruments mounted on the tripod took bottom photographs and measured such variables as water temperature, current velocity, and suspended-sediment concentration. FAT is used to better understand how and where deep-seafloor sediment moves and accumulates. Besides of this, we also use them to study the deep-sea biology. The obtained the images from the camera, the biology animals are hardly to be distinguished. In this project, we are concerned to use novel underwater imaging technologies for recovering the deep-sea scene.

    DOI Scopus

  • Touch switch sensor for cognitive body sensor networks

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

    Computer Communications    146   32 - 38   2019.10  [Refereed]

     View Summary

    © 2019 Elsevier B.V. With the global popularity of Internet of Things (IoT) technology, increasingly numbers of digital mobile products have been developed, and they have increased the productivity of people's daily lives. These electronic products are used in all aspects of life, such as medical care, office life, home services, and sports. However, most of these products are designed for healthy people with high literacy rates. For disabled people, these products cannot be widely used. In this paper, new, differently shaped touch sensors are proposed for body sensor network-based devices. This touch sensor can be formed into any shape because of the use of conductive fabric adhesive tape as a switch. That property is why the sensor can change positions in the body sensor network in which the human body is used as a trigger to safely activate the touch switch. The number of switch sensors can easily be increased or decreased without changing the wiring of the central controller. The number of sensors in a switch sensor system is greater than that in other touch switch systems, and the accuracy is higher.

    DOI Scopus

  • Segmentation of Bone Metastasis in CT Images Based on Modified HED

    Song Y., Lu H., Kim H., Murakami S., Ueno M., Terasawa T., Aoki T.

    International Conference on Control, Automation and Systems    2019-October   812 - 815   2019.10  [Refereed]

     View Summary

    © 2019 Institute of Control, Robotics and Systems - ICROS. Segmentation of the bone metastasis area in medical images can reduce the workload for diagnosis and treatment. However, there are various shapes and sizes of bone metastasis also affected by noise. As a result, it is difficult to segment using classical segmentation methods. In this paper, we propose a convolutional neural network model-based segmentation method. The proposed method easily predicts the contour and location of the lesion area using side connection and modified network. In this study, we modified again the modified HED network to match the characteristics of bone metastasis. The experimental results using the proposed method for segmenting bone metastasis in the lesion area has 79.8[%] of TP rate and 69.2[%] of IOU rate.

    DOI Scopus

  • Recognition of Surrounding Environment for Electric Wheelchair Based on WideSeg

    Sakai Y., Nakayama Y., Lu H., Li Y., Kim H.

    International Conference on Control, Automation and Systems    2019-October   816 - 820   2019.10  [Refereed]

     View Summary

    © 2019 Institute of Control, Robotics and Systems - ICROS. At present, the aging population is growing in Japan. Along with that, the expectation for the utilization of welfare equipment is increasing. Electric wheelchair, a convenient transportation tool, is popularized rapidly. On the other hand, accidents have occurred, and the dangers for driving are pointed out. Therefore, it needs to improve accident factors, reduce accidents and improve the convenience of electric wheelchair by automation. Environmental recognition is necessary for the development of autonomous electric wheelchair. Environmental recognition includes self-position estimation, recognition of sidewalks, crosswalks and traffic lights, moving object prediction, etc. In order to solve these various problems, this paper examines the segmentation of sidewalks, crosswalks and traffic lights. We develop the WideSeg that is one of semantic segmentation algorithms applying convolutional neural networks (CNN).

    DOI Scopus

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Publications (Books) 【 display / non-display

  • 医用画像解析ハンドブック

    金 亨燮 ( Joint Work )

    Ohmsha  2012.11

  • Artificial Intelligence and Robotics

    ( Joint Work )

    2017.09

  • Computational Anatomy Based on Whole Body Imaging

    ( Joint Work )

    2017.01

  • Technological Advancements in Biomedicine for Healthcare Applications

    Murakami, Kim, Tan, Ishikawa, Aoki ( Joint Work )

    IGI Global  2012.10 ISBN: 9781466621961

  • Object Tracking

    Sugandi,Kim,Tan,Ishikawa ( Joint Work )

    InTech  2011.02

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Conference Prsentations (Oral, Poster) 【 display / non-display

  • 実数値GAに基づく指骨CR画像の位置合わせ

    川越

    医療情報学連合大会  2018.11  -  2018.11 

  • R-FCNとGrowCutを用いたボールペンの検出

    毛利

    産業応用工学会全  2018.09  -  2018.09 

  • ResNetを用いた指骨CR画像からの骨粗しょう症の自動識別

    畠野

    日本医用画像工学会大会予稿集  (つくば大学)  2018.07  -  2018.07  日本医用画像工学会

  • 3次元Residual networks(ResNets)を用いた大腸CADにおける偽陽性陰影の識別

    植村

    日本医用画像工学会大会  2018.07  -  2018.07 

  • CNNによる胸部CT画像からの経時的差分画像上の異常陰影の検出

    長尾

    日本医用画像工学会大会  2018.07  -  2018.07  日本医用画像工学会

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Industrial Property 【 display / non-display

  • A voxel matching technique for removal of artifacts in medical subtraction images

    Industrial Property No a  UNITED STATES

Grants-in-Aid for Scientific Research 【 display / non-display

  • Development of a System for Spinal Deformity Detection Based on Moire Images

    Grant-in-Aid for Scientific Research(C)

    Project Year:  2006.04  -  2008.03

    Project Number:  18560414

  • CAD for temporal subtraction on thorax CT image

    Grant-in-Aid for Scientific Research on Priority Areas

    Project Year:  2005.04  -  2007.03

    Project Number:  17032009