TY - CHAP
T1 - Secured transmission of medical images in radiology using AES technique
AU - Prabhu, Pavithra
AU - Manjunath, K. N.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-04061-1_10
DO - 10.1007/978-3-030-04061-1_10
M3 - Chapter
AN - SCOPUS:85060224508
T3 - Lecture Notes in Computational Vision and Biomechanics
SP - 103
EP - 112
BT - Lecture Notes in Computational Vision and Biomechanics
PB - Springer Netherlands
ER -