Medical Image Tamper Detection Based on Passive Image Authentication.

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious co...

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Publicado en:Journal of Digital Imaging Vol. 30; no. 6; pp. 695 - 710
Autores principales: Ulutas, Guzin, Ustubioglu, Arda, Ustubioglu, Beste, Nabiyev, Vasif, Ulutas, Mustafa
Formato: diagnostic images equations & formulas pictorial tables/charts Journal Article
Publicado: Springer Nature Dec2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2017
      vid: 30
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-017-9961-x
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        atl: Medical Image Tamper Detection Based on Passive Image Authentication.
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        au:
          Ulutas, Guzin
          Ustubioglu, Arda
          Ustubioglu, Beste
          Nabiyev, Vasif
          Ulutas, Mustafa
        affil: Computer Engineering Department , Karadeniz Technical University , Trabzon Turkey
      sug:
        subj:
          Diagnostic Imaging
          Telemedicine
          Teleradiology
          Data Security Methods
          Internet
          Image Processing, Computer Assisted
          Quality Assurance
          Access to Information
          Information Management
      ab: Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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