Preferred Language
Articles
/
bhcwiJIBVTCNdQwCCLO-
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
...Show More Authors

Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascaded-looking composition of F-functions in a quadrate architecture. The proposed F-function architecture is a three-input, three-output Type-3 AES-Feistel network with additional integer parameters representing the subkeys in use. The suggested system makes use of the AES block cipher as a function on a Type-3 AES-Feistel network. Blocks in the proposed system are 896 bits in length, whereas keys are 128 bits. The production of subkeys is encrypted using a chain of E8- algorithms. The necessary subkeys are then generated with a recursion. The results are reviewed to verify that the new layout improves the security of the AES block cipher when used to encrypt medical images in a computer system.

Crossref
View Publication
Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
...Show More Authors

View Publication
Scopus (15)
Crossref (6)
Scopus Crossref
Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
...Show More Authors

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing
...Show More Authors

Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
...Show More Authors

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

... Show More
Preview PDF
Publication Date
Fri May 17 2013
Journal Name
International Journal Of Computer Applications
Applied Minimized Matrix Size Algorithm on the Transformed Images by DCT and DWT used for Image Compression
...Show More Authors

View Publication
Crossref (1)
Crossref
Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Image Steganography using Dynamic Threshold based on Discrete Cosine Transform
...Show More Authors

The art of preventing the detection of hidden information messages is the way that steganography work. Several algorithms have been proposed for steganographic techniques. A major portion of these algorithms is specified for image steganography because the image has a high level of redundancy. This paper proposed an image steganography technique using a dynamic threshold produced by the discrete cosine coefficient. After dividing the green and blue channel of the cover image into 1*3-pixel blocks, check if any bits of green channel block less or equal to threshold then start to store the secret bits in blue channel block, and to increase the security not all bits in the chosen block used to store the secret bits. Firstly, store in the cente

... Show More
View Publication Preview PDF
Scopus (6)
Crossref (4)
Scopus Crossref
Publication Date
Wed Apr 20 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Text image secret sharing with hiding based on color feature
...Show More Authors

View Publication
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
...Show More Authors

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

View Publication
Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
...Show More Authors

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

... Show More
View Publication Preview PDF
Scopus (7)
Crossref (5)
Scopus Crossref
Publication Date
Tue Feb 28 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Implementation of EEG-Based Smart Structure
...Show More Authors

View Publication
Scopus (6)
Crossref (1)
Scopus Crossref