Prediction-Based Reversible Watermarking for Safe Transfer of CT Scan Medical Images

Author(s):  
Nisar Ahmed Memon ◽  
Shakeel Ahmed
Author(s):  
Sudhir Tirumalasetty ◽  
J. Sri Latha ◽  
J. Neeharika ◽  
L. Sri Pravallika ◽  
M. Manasa

Most of the patient diagnosis revolves around in identifying abnormalities in their respective medical images. These images are of various types, likely Ultrasound, CT scan, MRI and microscopic images like bio-chemical slides, micro-biological slides & pathological slides. Few abnormalities are fractures, bad cells in blood, tumors, fungal identification etc. Finding the abnormal portions in these images needs expertise by the physician; this apt identification promotes and guarantees healthy medication by the physician or surgeon to patient. In medical microscopic images normal portions and abnormal portions are mixed together. None of the abnormal portions are related to abnormal and normal portions of image i.e. deviations are scattered among normal portions of image. These deviations are not present in some portions for specific area in the images. None of these deviations are overlapped nor can be grouped together into a single portion physically in the image. Deviations are isolated along with normal portions of images. Identifying such deviations is vital. In previous methods these deviations are identified used BFS and Shortest Path Algorithm. This paper focuses on identifying deviations using parallel computing applied over fragmented portions of blood images using divide and conquer.


2020 ◽  
Vol 10 (6) ◽  
pp. 1288-1293
Author(s):  
K. N. Madhusudhan ◽  
P. Sakthivel

The image authentication is generally based on two different types of techniques: watermarking and digital signature. In watermarking methods, embedded watermarking is often imperceptible and it contains either a specific ID of producer or codes related to content that are used for authentication. Normally a separate file is stored, digital signature is a non-repudiation and encrypted version of the information extracted from the data. A digital signature can be attached to the data to prove the originality and integrity. The proposed work presents a new approach to steganography of medical images that uses modified Least Significant Bit (LSB) based on the Local Binary Pattern (LBP) pattern. As a first step, cover image has been divided as blocks of 3×3 non overlapping masks. Then, the pixel embedding position (clock wise or anti-clock wise) has to be identified using LBP operator. The value of the LBP operator determines how and where to embed secret image pixel. Later, using LSB method, pixel values will be embedded in the cover image pixel. In order to provide the integrity of the data, the proposed work also presents Reversible Watermarking (RW), a Digital Signature (DS) technique. The proposed algorithm of steganography experimented on few medical images and achieved better efficiency with respect to MSE and PSNR values and same is reported in this paper.


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