Mona M. Soliman

Treatment of genital warts in males by pulsed dye laser

Objective: To determine the safety and efficacy of the flashlamp‐pumped pulsed dye laser for the treatment of uncomplicated genital warts in adult males. Methods: This was a prospective observational study set in the outpatient clinics of the Department of Andrology and Sexually Transmitted Diseases, National Institute of Laser Enhanced Sciences, the Dermatology Clinic, Cairo University, and the Department of Dermatology and Venereology, Suez Canal University. A total of 174 adult male patients with 550 uncomplicated anogenital warts were included. Selective photothermolysis and photocoagulation of the lesions with the flashlamp‐pumped pulsed dye laser was carried out. A pulsed dye laser (wavelength 585 nm, 450 s pulse duration; Cynosure, USA) was used with the following settings: spot size 5–7 mm; fluence 9–10 J/cm2. Results: Complete resolution of treated warts was achieved in 96% of lesions. Side effects were limited, transient and infrequent. Lesion recurrence rate was 5%. Conclusion: The pulsed dye laser has been found to be safe, effective and satisfactory for the treatment of anogenital warts in males. It could be used to selectively destroy warts without damaging the surrounding skin.

An adaptive watermarking approach based on weighted quantum particle swarm optimization

Abstract In this paper, we propose a novel optimal singular value decomposition (SVD)-based image watermarking approach that uses a new combination of weighted quantum particle swarm optimization (WQPSO) algorithm and a human visual system (HVS) model for both the hybrid discrete wavelet transform and discrete cosine transform (DCT). The proposed SVD-based watermarking approach initially decomposes the host image into sub-bands; afterwards, singular values of the DCT of the lower sub-band of the host image are quantized using a set of optimal quantization steps deduced from a combination of the WQPSO algorithm and the HVS model. To evaluate the performance of the proposed approach, we present tests on different images. The experimental results show that the proposed approach yields a watermarked image with good visual definition; at the same time, the embedded watermark was robust against a wide variety of common attacks, including JPEG compression, Gaussian noise, salt and pepper noises, Gaussian filters, median filters, image cropping, and image scaling. Moreover, the results of various experimental analyses demonstrated the superiority of the WQPSO approach over other optimization techniques, including classical PSO and QPSO in terms of local convergence speed, resulting in a better balance between global and local searches of the watermarking algorithm.

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

Bio-inspired Swarm Techniques for Thermogram Breast Cancer Detection

Bio-inspired swarm techniques are a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. These techniques involving the study of collective behavior in decentralized systems. Such systems are made up by a population of simple agents interacting locally with one other and with their environment. The system is initialized with a population of individuals (i.e., potential solutions). These individuals are then manipulated over many iteration steps by mimicking the social behavior of insects or animals, in an effort to find the optima in the problem space. A potential solution simplifies through the search space by modifying itself according to its past experience and its relationship with other individuals in the population and the environment. Problems like finding and storing foods, selecting and picking up materials for future usage require a detailed planning, and are solved by insect colonies without any kind of supervisor or controller. Since 1990, several collective behavior (like social insects, bird flocking) inspired algorithms have been proposed. The objective of this article is to present to the swarms and biomedical engineering research communities some of the state-of-the-art in swarms applications to biomedical engineering and motivate research in new trend-setting directions. In this article, we present four swarms algorithms including Particle swarm optimization (PSO), Grey Wolf Optimizer (GWO), Moth Flame Optimization (MFO), and Firefly Algorithm Optimization (FA) and how these techniques could be successfully employed to tackle segmentation biomedical imaging problem. An application of thermography breast cancer imaging has been chosen and the scheme have been applied to see their ability and accuracy to classify the breast cancer images into two outcomes: normal or non-normal.

An adaptive medical images watermarking using Quantum Particle Swarm Optimization

Quantum Particle Swarm Optimization (QPSO) in the field of medical image watermarking for copyright protection and authentication. The trade-off between the imperceptibility and robustness is one of most serious challenges in digital watermarking system. To solve the problem, image watermarking can be considered as an optimization problem by utilizing human visual system (HVS) characteristics and QPSO algorithm in adaptive quantization index modulation and singular value decomposition in conjunction with discrete wavelet transform (DWT) and discrete cosine transform (DCT). Experimental results prove the effectiveness of the proposed algorithm that yields a watermarked image with good visual fidelity, at the same time watermark able to withstand a variety of attacks including JPEG compression, Gaussian noise, Salt and Pepper noises, Gaussian filter, median filter, image cropping and image scaling.

A Robust 3D Mesh Watermarking Approach Using Genetic Algorithms

This paper proposes a new approach of 3D watermarking by ensuring the optimal preservation of mesh surfaces. The minimal surface distortion is enforced during watermark embedding stage using Genetic Algorithm (GA) optimization. The watermark embedding is performed only on set of selected vertices come out from k-means clustering technique. These vertices are used as candidates for watermark carriers that will hold watermark bits stream. A 3D surface preservation function is defined according to the distance of a vertex displaced by watermarking to the original surface. A study of the proposed methodology has high robustness against the common mesh attacks while preserving the original object surface during watermarking.

Robust watermarking approach for 3D triangular mesh using self organization map

The objective of this paper is to explore innovative ways to insert the maximum amount of secret information into 3D mesh models without causing perceptual distortion and also make it difficult for the attacker to guess where the watermark was inserted. It is based on clustering 3D vertices into appropriate or inappropriate candidates for watermark insertion using Self Organization Map (SOM). Two methods were used to embed the watermark into 3D model. The first method is a statistical approach that modified the distribution of vertex norms to hide watermark information into host 3D model while the second method is a mixed insertion of watermark bits into host model using vertex norm distribution and mesh vertices at the same time. The robustness of proposed techniques is evaluated experimentally by simulating attacks such as mesh smoothing, noise addition and mesh cropping.

A study of the treatment of cutaneous fungal infection in animal model using photoactivated composite of methylene blue and gold nanoparticle

BACKGROUND Onychomycosis is a widespread public health problem, in which T. rubrum and T. mentagrophytes is the commenest causative organisms. Current medical therapy has many drawbacks and side effects. Methylene blue (m.b) photodynamic therapy (pdt) proved efficacy but with lengthy sessions. OBJECTIVES Optimizing methylene blue photodynamic therapy by combination of methylene blue photosensitizer and gold nanoparticles (aunps) in a composite as gold nanoparticles are efficient delivery systems and efficient enhancers of photosensitizers for antifungal photodynamic therapy. MATERIALS AND METHODS Eighty newzealand rabbit (Oryctolagus cuniculus) were used and categorized in eight equal groups as follows; healthy and infection control, composite photodynamic therapy and five comparative groups. Photodynamic therapy was initiated at day three to five post inoculation, for four sessions forty eight hours apart. Each group divided and light exposure at two fluencies; 80J and 100J. All groups were investigated macroscopically and microscopically (histopathology and scanning electron microscope) also flowcytometry assessment for cell death and X-ray analysis for gold nanoparticles accumulation in brain and liver tissues were determined. RESULTS Recovery from infection approaching 96% in gold nanoparticles+light group, around 40% in methylene blue photodynamic therapy and 34% in composite photodynamic therapy. The observed findings confirmed by apparent decrease of apoptosis, however small amounts of gold nanoparticles detected in brain and liver. CONCLUSION Light stimulated gold nanoparticles is a promising tool in treatment of onychomycosis.

A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods

Blind and robust watermarking of 3D mesh aims to embed message into a 3D mesh model such that the mesh is not visually distorted from the original model. An essential condition is that the message should be securely extracted even after the mesh model was processed. This paper explores use of artificial intelligence techniques to build blind and robust 3D-watermarking approach. It is based on clustering 3D vertices into appropriate or inappropriate candidates for watermark insertion using K-means clustering and Self Organization Map (SOM) clustering algorithms. The watermark insertion were performed only on set of selected vertices come out from clustering technique. These vertices are used as candidates for watermark carriers that will hold watermark bits stream. Through the simulations, the authors prove that the proposed approach is robust against various kinds of geometrical attacks such as mesh smoothing, noise addition and mesh cropping. A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods

The Way of Improving PSO Performance: Medical Imaging Watermarking Case Study

Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are population based heuristic search techniques which can be used to solve the optimization problems modeled on the concept of evolutionary approach. In this paper we incorporate PSO with GA in hybrid technique called GPSO. This paper proposes the use of GPSO in designing an adaptive medical watermarking algorithm. Such algorithm aim to enhance the security, confidentiality , and integrity of medical images transmitted through the Internet. The experimental results show that the proposed algorithm yields a watermark which is invisible to human eyes and is robust against a wide variety of common attacks.