Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks
As computed tomography image (<italic>CTI</italic>) sequence can be regarded as a medical image set, which contains several neighboring and visually similar <italic>CTI</italic> s with temporal information, conducting an efficient similarity retrieval of the large <italic&...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9784837/ |
| _version_ | 1818206788905861120 |
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| author | Yi Zhuang Nan Jiang |
| author_facet | Yi Zhuang Nan Jiang |
| author_sort | Yi Zhuang |
| collection | DOAJ |
| description | As computed tomography image (<italic>CTI</italic>) sequence can be regarded as a medical image set, which contains several neighboring and visually similar <italic>CTI</italic> s with temporal information, conducting an efficient similarity retrieval of the large <italic>CTI</italic> sequences poses great challenge. Finding the similar <italic>CTI</italic> sequences can assist diagnosis and treatment by allowing physicians to quickly locate pathological images of lesion tissues, accurately find the source of disease. The paper proposes a progressive <italic>P</italic>rivacy-preserving similarity <italic>R</italic>etrieval scheme for the <italic>CTI</italic> <italic>S</italic>equences in the mobile telemedicine network (<italic>MTN</italic>) called the <italic>P RS</italic> method. To better facilitate the <italic>P RS</italic> processing, five enabling techniques are devised: 1) <italic>key CTI (KCTI)-based similarity measure</italic>, 2) <italic>local privacy preserving scheme</italic>, 3) <italic>zero-distance</italic> (<italic>ZD)-based distributed storage scheme</italic>, 4) <italic>uniform distributed index framework</italic>, and <italic>5</italic>) <italic>crowd-assisted verification</italic>. Extensive experiments demonstrate that the retrieval efficiency of our proposed <italic>P RS</italic> method is about 90% higher than that of the existing ones. |
| first_indexed | 2024-12-12T04:18:36Z |
| format | Article |
| id | doaj.art-ba53a39d4f8547108e28d3c0181f102a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-12T04:18:36Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ba53a39d4f8547108e28d3c0181f102a2022-12-22T00:38:23ZengIEEEIEEE Access2169-35362022-01-0110573395735110.1109/ACCESS.2022.31787059784837Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine NetworksYi Zhuang0https://orcid.org/0000-0001-6465-4634Nan Jiang1School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, ChinaAffiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaAs computed tomography image (<italic>CTI</italic>) sequence can be regarded as a medical image set, which contains several neighboring and visually similar <italic>CTI</italic> s with temporal information, conducting an efficient similarity retrieval of the large <italic>CTI</italic> sequences poses great challenge. Finding the similar <italic>CTI</italic> sequences can assist diagnosis and treatment by allowing physicians to quickly locate pathological images of lesion tissues, accurately find the source of disease. The paper proposes a progressive <italic>P</italic>rivacy-preserving similarity <italic>R</italic>etrieval scheme for the <italic>CTI</italic> <italic>S</italic>equences in the mobile telemedicine network (<italic>MTN</italic>) called the <italic>P RS</italic> method. To better facilitate the <italic>P RS</italic> processing, five enabling techniques are devised: 1) <italic>key CTI (KCTI)-based similarity measure</italic>, 2) <italic>local privacy preserving scheme</italic>, 3) <italic>zero-distance</italic> (<italic>ZD)-based distributed storage scheme</italic>, 4) <italic>uniform distributed index framework</italic>, and <italic>5</italic>) <italic>crowd-assisted verification</italic>. Extensive experiments demonstrate that the retrieval efficiency of our proposed <italic>P RS</italic> method is about 90% higher than that of the existing ones.https://ieeexplore.ieee.org/document/9784837/Computed tomography imageprivacy preservingmobile telemedicine networksimilarity retrieval |
| spellingShingle | Yi Zhuang Nan Jiang Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks IEEE Access Computed tomography image privacy preserving mobile telemedicine network similarity retrieval |
| title | Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks |
| title_full | Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks |
| title_fullStr | Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks |
| title_full_unstemmed | Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks |
| title_short | Privacy-Preserving Distributed Similarity Retrieval of Large CT Image Sequence Database in Mobile Telemedicine Networks |
| title_sort | privacy preserving distributed similarity retrieval of large ct image sequence database in mobile telemedicine networks |
| topic | Computed tomography image privacy preserving mobile telemedicine network similarity retrieval |
| url | https://ieeexplore.ieee.org/document/9784837/ |
| work_keys_str_mv | AT yizhuang privacypreservingdistributedsimilarityretrievaloflargectimagesequencedatabaseinmobiletelemedicinenetworks AT nanjiang privacypreservingdistributedsimilarityretrievaloflargectimagesequencedatabaseinmobiletelemedicinenetworks |