كوثر حسن صاحب الخفاجي

Considering the rapid development of digital communications technologies and the massive distribution of multimedia images, the need to prevent sensitive content of images to unlawful use has become a core requirement. The same can be applied to medical imaging, as intensity values and spatial positioning of adjacent pixels are strongly interdependent. The described technique modifies the natural pixel correlation by increasing the positional and intensity entropy with the help of row and column permutation. Experimental tests proved that the algorithm is able to encode and decode pictures with a private key without any danger. Even though the encryption algorithm is computationally efficient and easy to execute, it is invulnerable to possible cryptographic attacks. The investigation utilized a range of performance indicators, such as Encryption Duration (ET), Decryption Duration (DT), and the Information Entropy of the original image (Eo).

The rapid advancement of medical technologies has led to a substantial increase in the acquisition and storage of medical images, particularly through techniques such as computed tomography (CT). This growth highlights the need for effective image processing algorithms that can support physicians in diagnosing and evaluating medical conditions more efficiently. Among these approaches, medical image colorization has attracted growing interest in recent years. Unlike traditional grayscale images, synthesized color images can provide enhanced visual information about organs and tissues, thereby improving image interpretation. In this study, a novel mathematical approach is proposed to enhance the quality of CT scan images using trigonometric functions governed by three main parameters, using MATLAB software. The experimental results demonstrate that improving color contrast contributes to a more accurate distinction between different tissues and organs, offering clearer visual representation and supporting analytical as well as diagnostic processes. The evaluation by radiology experts indicated a significant improvement in the quality of the enhanced images, supporting the quantitative assessment results and confirming the effectiveness of the proposed method.

The most widely used technique for imaging soft tissues such as tumors, or brain and spinal cord disorders is magnetic resonance imaging (MRI). Nevertheless, the inherent loss of contrast in these images impacts proper clinical interpretation and diagnostic efficiency. The objective of this study to develop the method for better MRI images using an algorithm based on mathematical functions, which contains three main parameters: F, P and N in MATLAB environment. The resulting color images exhibit increased contrast of pathologic regions, increasing the clarity of tumor borders and revealing fine anatomical features. The algorithm’s performance was evaluated using standard quality metrics, and the results showed a significant improvement in the visual interpretation of the images. the results confirm that the proposed algorithm is capable of improving the quality of MRI images and highlighting tumors, making it a promising tool for supporting more accurate medical diagnosis.

To study the tracks of the alpha particles, his study is based on the digital image processing techniques associated with the theoretical model of the Bethe-Bloch equation, which describes the tracks of alpha particles. His study aims to characterize the physical and morphological properties of alpha-particle tracks with a good precision, a task accomplished through the use of digital image processing techniques, and with the aid of the theoretical model of the tracks of the alpha particles, the Bethe-Bloch equation. Only a few tracks were found and the mean diameter of 23 µm shows a relatively large standard deviation, indicating that the size of the tracks is quite variable. Morphological analysis showed that the tracks were not circular but elongated or irregular, and the three-dimensional visualization showed that there were significant correlations between physical morphology and track density. The etch-rate ratio further was near to unity, indicating uniform etching conditions, and the theoretical energy loss (5900 MeV/cm) was in good agreement with the model. All these results clearly show that the combination of image processing, statistics and shape analysis with theoretical modelling is a powerful tool for understanding the behavior of alpha particles and hence it can be useful for applications in nuclear physics and radiation dosimetry

Abstract: The neurological form of Taenia solium is the most important cause of acquired epilepsy and the larvae of T. solium cause cysticercosis, which is a significant public health problem. The current diagnosis method is based on radiology exam and may take time and be subjective, particularly in resource-limited areas. In this study, we introduce an automated framework of image processing algorithms based on MATLAB to detect soft-tissue calcifications indicative of cysticercosis on simple X-ray images. This pipeline consists of preprocessing, metallic-implant exclusion, local-contrast enhancement, robust thresholding, geometric feature extraction and lesion classification as rice-grain-type calcifications or ring-calcified masses. The case level indices (lesion density, orientation coherence, and midline distribution) are combined together to get a composite evidence score and automatically diagnose the cases. When applied to a representative radiograph, the algorithm identified 162 rice-grain-like calcifications with even distribution across the midline (0.99) and low value for orientation coherence (R = 0.19) and hence a heuristic composite score (52.1/100) and an impression of "pattern compatible with cysticercosis, alternatives not excluded". The nominal measurements are absolute and there was no diagnostic accuracy claimed as the source image was not spatially calibrated and there was no reference standard available. The findings in this study show the technical feasibility of automating the initial stages of the soft-tissue calcification characterisation process, which are quantitative and reproducible, and outline the validation steps needed before any consideration of a decision support role

Airway management is a critical pillar of an aesthetic and surgical practice. Any unforeseen airway obstruction during clinical procedures can lead to severe complications, including acute hypoxia or cardiac arrest. This study aims to highlight the pivotal role of advanced medical imaging as a diagnostic and proactive tool for evaluating the complex anatomy of the upper airway and predicting potential challenges during tracheal intubation. The study adopted an analytical approach by examining clinical cases from multiple medical centres, including Al-Sadr Teaching Hospital, Al-Najaf Teaching Hospital and the National Oncology Hospital. The sample encompassed various conditions, such as structural deformities, nasal septum deviation, and laryngeal tumours. The imaging protocols utilised included Computed Tomography (CT) for its superior visualisation of osseous structures, Magnetic Resonance Imaging (MRI) for precise softtissue characterisation, and conventional X-ray radiography. The findings indicate that integrating traditional clinical assessment with radiographic data effectively identifies obstructive factors, such as tonsillar hypertrophy, macroglossia, or airway narrowing associated with obesity. The study concludes that reliance on advanced imaging modalities significantly reduces the incidence of life-threatening events during anaesthesia, thereby enhancing patient safety standards and facilitating the development of precise contingency plans for difficult airway management.

ءThe procedure for securely transferring encrypted images over the network so that an unauthorized user cannot decrypt them is by implementing strong algorithms that cannot be decrypted. There are different methods and multiple algorithms for encrypting and decrypting images. The most common way to encrypt images is the Chaotic Image System. The encryption key and decryption key are called the “symmetric key." In this research, a medical researcher found that the chaotic logistic encryption algorithm has a better effect on encrypting medical X-ray image information and hides the statistical properties of the original medical encryption. Several standards were used to measure image quality during and after encryption, and a comparison was made between them to obtain optimal values for encrypting the X-ray image. The correlation relationship between the adjacent pixels of both the original and the encrypted image was also measured at both values of the initial coefficients. The correlation relationship for the adjacent pixels in the original image was found to be strong. However, in the case of the encrypted image, it is sparse and has little correlation. Finally, in the case of the image in which encryption does not occur, the correlation relationship between adjacent pixels is similar to the original image. Several measurements were used in the research, such as Encryption Time (ET), Decryption Time (DT), and Information Entropy for the Original image (Eo)

The most often requested test in every radiology department, chest X-rays are crucial for the diagnosis of several chest conditions. Despite the numerous technological advancements in radiology, interpreting a chest X-ray remains a challenging task because of the images' propensity for noise, low contrast, and blurriness. Additionally, extraneous information obstructs the analysis of actual issues with human chest structures, making it challenging to analyze X-ray images effectively. In this study, we used a novel algorithm to improve digital chest radiographs and, consequently, improve the diagnosis of specific diseases. We achieved this by applying a number of procedures, such as enhancing the fundamental features of the images and refining the colors by using an experimental equation and varying the values of the equation's primary parameter. The ribs, sternum, and clavicle, as well as the soft tissues, were all clearly visible in the final images that we examined, which is a positive sign that the suggested algorithm improved the diagnosis. Because there are many hacking operations and instances of personal and medical information being stolen, these medical pictures in the modern world of telemedicine need to be safeguarded from users who are not permitted to see the information contained in them. Given that the figure illustrates the connections between the pixels, the chaotic logistic encryption algorithm-based picture encryption technique has been used. contiguous to confirm this encryption algorithm's encryption effectiveness. Use MATLAB to show the encryption in order to illustrate how the method affects the encrypted picture data. picture analysis naturally discovers that the chaotic logistic encryption method performs better at encrypting picture data. Additionally, the statistical data successfully obscures the original image's features, making it resistant to statistical assaults based on image pixel values. This technique was used on encrypted medical images, and a value of 4 falls within the encryption range.

An image encryption method based on the chaotic logistic encryption algorithm was applied on Xray medical image, using the histogram of the X-ray image and the plot showing the correlation between adjacent pixels to verify the encryption effect of this encryption algorithm. In order to reflect the effect of the algorithm in encrypting image information, use MATLAB to display the encryption. Subsequent image and histogram analysis can intuitively find that the chaotic logistic encryption algorithm has a better effect on encrypting image information, and the statistical data well hides the characteristics of the original image, which can effectively resist statistical attacks based on image pixel values. Image encryption effect and multiple image quality metrics are applied to verify the encryption effect of this encryption algorithm, this method was applied to medical images of the type of X-ray Through the application of a number of image quality standards, the extent of the influence of the parameter X.

Abstract: Encryption and decryption play a significant job in the development of the image stockpiling. It is used to achieve the mains of security objectives like secrecy, confirmation, honesty, integrity, and non-renouncement. In this paper we apply an optical scanning cryptography for encryption and decryption on three different type of (binary, grayscale & color) images. It is found that simulation process was great and successful in encrypting all these images, as well as it furnishes protection and security with every step of the optical encryption method

In this paper, a computer simulation of optical encryption for color images are presented based on the optical scanning cryptography technique that T.C. Poon suggested in 2003. This method is based on using an encryption key; the color image is optically encrypted. The output is a signal at a radio frequency which it transmits to a receiver (secure site) via an antenna for digital storage and decryption. To create an electrical signal, the same optical scanning system is employed in the secure site, along with a decryption key. After that, the electrical signal is analyzed and transferred to a computer for decryption; a digital decryption unit performs a decryption algorithm. The electrical signal is then analyzed and delivered to a computer for decryption, where a decryption procedure is performed by a digital decryption unit. The decryption unit will decrypt the color image if the encryption and decryption keys are identical. To ensure the system’s effectiveness, by applying several image quality measures to measure the quality of the recovered image (after encryption). The encryption result indicates that the proposed technique produces a noise-like structure that reveals no useful information about the original image.

The aim of this paper is to realize the antibiotic resistance in agar diffusion test, the agar medium is including varies wafers containing antibiotics, each antibiotic has a different response to the bacterium ,therefore, the size of inhibition zone of the standard antibiotics are different in each case, to demonstrate the suitability of antibiotics for utilize, we tend to measure the diameter of inhibition zones by using the Matlab functions that come with the image processing Toolbox to measuring the inhibition zones diameter in an images accurately and compare these values with the Standard tables

Hydatid disease is an important zoonotic parasitic disease with public health significance that affects both humans and other mammals such as sheep, dogs, rodents and horses, currently the surgery is the best way for treatment in hydatid Cysts, a major concern during surgery to remove cysts is that brood capsules can float free within the cyst and that lead to spillage of viable parasite (Protoscolices), Therefore the surgeons inject the cyst by Scolicidal agent before removing the cyst and that lead to killing most or in some time all the Protoscolices in the cyst. The aim of current research is to produce a an effective image processing program that can detect and separate the Protoscolices of hydatid cysts dead from live in the microscopic medical image ,depending on color detection technique by using Matlab image processing function and tools .The results indicate that the algorithm proposed are able to isolate the dead Protoscolices in hydatid cysts microscopic images.

In this paper we investigate the effect of image size on the compression parameters of the fractal image compression technique(FIC) proposed by Jacquin This research is tested on 8 bits/pixel gray images, three different size of gray image have been used (100 x 100, 150 x 150 ,256 x256). The results show that the PSNR, Bit Rate and Encoding time are increase with the increase of image size, but the CR is decreases with the increase of image size, The quality of the reconstructed image is pleasurable either we use any size of images .

in this work we study the effect of quantization process on the reconstructed image in fractal image compression FIC method. This method is tested on 8 bits/pixel gray image. The test results conducted on Lena image indicated that the quantization increases compression ratio about (65.8%) and encoding time about (17.1%) but the decreases of PSNR around (1.73%), The quality of the reconstructed image is good either we use the quantization process or not.

this work is show the effect of quantization on the reconstructed image in fractal image compression FIC method. it is based on zero-mean block matching method, at this method the mean of the range blocks is used instead of traditional offset parameter. This reduces and simplifies the computations of the affine parameters during the encoding process. This method is tested on 8 bits/pixel gray image. The test results conducted on Lena image indicated that the quantization increases compression ratio about (69.6%) and encoding time about (18.6%) but the decreases of PSNR around (0.3%), The quality of the reconstructed image is good either we use the quantization process or not used it.

This paper studies the effect of symmetry process on the compression parameters of the fractal image compression tech-nique proposed by Jacquin. Two kinds of tests have been conducted. The first all kind of the symmetry operations [0-7] were taken; while the second tests were concentrated on studying the effect of the following parameters Block Size, Step Size, Domain Size on the probability distribution of symmetry operation. The results show that the higher value of PSNR and the lower value of ET occur at even symmetry operation only, but compression ratio is not affected with symmetry process. Also the occurrence probability of even symmetry is more than odd symmetry for all compression parameters. This behaviour can be utilized to reduce the encoding time to 50% with preserving PSNR