Secured transmission of medical images in radiology using AES technique

Pavithra Prabhu, K. N. Manjunath

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Medical imaging technology results in more than thousands of images per patient and transmitting them securely over an insecure network is a challenging task still. Maintaining the data integrity against intruder is important. This paper discusses a hybrid method which combines image processing and cryptography to make sure that all images are securely transmitted. In the proposed method, a Digitally Reconstructed Radiograph (DRR) is generated from all the images of a 3D volume of the patient, and then divided the DRR image into four equal quadrants. The zigzag pattern was applied to all these sixteen quadrants. Each quadrant was separately encrypted in block cipher mode using AES algorithm. At the receiver side, the DRR was regenerated from all the transmitted images and was compared with the deciphered blocks using histogram comparison of each block. The method was applied to CT images of 40 patients of brain tumor, CT colonography, and nasopharynx dataset. The image injection techniques were applied and tested the result with the addition of image, deletion of an image and through modification of Hounsfield values.

Original languageEnglish
Title of host publicationLecture Notes in Computational Vision and Biomechanics
PublisherSpringer Netherlands
Pages103-112
Number of pages10
DOIs
Publication statusPublished - 01-01-2019

Publication series

NameLecture Notes in Computational Vision and Biomechanics
Volume31
ISSN (Print)2212-9391
ISSN (Electronic)2212-9413

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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence

Cite this

Prabhu, P., & Manjunath, K. N. (2019). Secured transmission of medical images in radiology using AES technique. In Lecture Notes in Computational Vision and Biomechanics (pp. 103-112). (Lecture Notes in Computational Vision and Biomechanics; Vol. 31). Springer Netherlands. https://doi.org/10.1007/978-3-030-04061-1_10