Micro and Nanosystems - Online First

Tremendous developments in multimedia technology have promoted a massive amount of research in image and video processing. As imaging technologies are rapidly increasing, it is becoming essential to use images in almost every application in our day-to-day life.

This paper presents a comparative analysis of various image restoration approaches, ranging from fundamental methods to advanced techniques. These approaches aim to improve the quality of images that have been degraded during acquisition or transmission. A brief overview of the image restoration approaches is mentioned in the paper, which are as follows:

Wiener Filter: The Wiener filter is a classical approach used for image restoration. It is a linear filter that minimizes the mean square error between the original image and the restored image. Inverse Filter: The inverse filter is another traditional restoration technique. It attempts to invert the degradation process to recover the original image. However, inverse filtering is highly sensitive to noise and tends to amplify noise artifacts. Linear and Nonlinear Filtering: These methods involve applying linear or nonlinear filters to the degraded image to enhance its quality. Linear filters, such as Gaussian filters, can effectively reduce noise but may blur the image. Nonlinear filters, such as median filters, can preserve edges while reducing noise. Compressive Sensing (CS) Restoration Approaches: Compressive sensing is a signal processing technique that exploits the sparsity of signals or images to reconstruct them from fewer measurements. CS-based restoration methods aim to recover high-quality images from compressed or incomplete measurements. Neural Networks Approaches: With the advancements in deep learning, neural networks have been widely used for image restoration tasks. Convolutional neural networks (CNNs) and generative adversarial networks (GANs) have shown promising results in restoring degraded images by learning from large datasets.

The paper likely provides a detailed analysis and comparison of these approaches, highlighting their strengths, weaknesses, and performance in different scenarios.

This paper aims to improve the quality of restored images. Several image restoration approaches have been compared, and they have exhibited enhanced performance compared to several existing image restoration approaches.

The development of more effective drug delivery techniques is necessary to increase treatment efficacy and patient compliance since tuberculosis (TB) is still a serious worldwide health concern. Ethambutol is a vital aspect of TB treatment, and using nanoparticles to carry it to the lungs may provide targeted delivery and prolonged release, which might enhance the effectiveness of the treatment.

This work aimed to optimize the formulation for prolonged drug release by synthesizing and assessing ethambutol-loaded nanoparticles using the desolation technique with albumin as the polymer. Additionally, the effects of different drug-polymer ratios and stirring rates were investigated.

Nine formulations of ethambutol-loaded nanoparticles were prepared by varying the drug-polymer ratios (1:1 to 1:2) and stirring speeds (500 to 1500 rpm). Key parameters, such as particle size, drug entrapment efficiency, and zeta potential, were measured. The optimized formulation was selected based on the smallest particle size and highest drug entrapment efficiency. Scanning electron microscopy was used to analyze the surface morphology of the nanoparticles. The in vitro drug release profile of the optimized formulation was studied over 24 hours.

Increasing the drug-polymer ratio from 1:1 to 1:2 increased nanoparticle size from 192.1 nm to 605.06 nm and decreased drug entrapment efficiency from 75.7%±0.08 to 34%±0.06. Higher stirring speeds (500 to 1500 rpm) also led to larger particle sizes and reduced drug entrapment due to polymer self-aggregation. Zeta potential values ranged from -5.56 to -25.6 mV. Scanning electron microscopy confirmed smooth, spherical nanoparticles. The optimized formulation, EN-5, exhibited the smallest particle size and highest drug entrapment efficiency. In vitro drug release studies showed a sustained ethambutol release, with 42.66±1.53% released in 12 hours and 79.082±2.98% in 24 hours.

Ethambutol-loaded nanoparticles having the ability to transport drugs to the lungs over an extended period of time were developed and optimized in the study. With improved drug delivery systems, the optimized formulation showed notable drug entrapment efficiency and controlled release, suggesting its potential to improve tuberculosis therapy.