Brain tumor classification is a crucial task to evaluate the tumors and make treatment decision according their classes. There are many imaging techniques used detect brain tumors. However, MRI commonly due its superior image quality fact of relying on no ionizing radiation. Deep learning (DL) subfield machine recently showed remarkable performance, especially in segmentation problems. In this paper, DL model based convolutional neural network proposed classify different types using two...

Breast cancer, with its high incidence and mortality globally, necessitates early prediction of local distant recurrence to improve treatment outcomes. This study develops validates predictive models for breast cancer metastasis using Recurrence-Free Survival Analysis machine learning techniques. We merged datasets from the Molecular Taxonomy Cancer International Consortium, Memorial Sloan Kettering Center, Duke University, SEER program, creating a comprehensive dataset 272, 252 rows 23...

The coronavirus disease 2019 (COVID-19) pandemic has been spreading quickly, threatening the public health system. Consequently, positive COVID-19 cases must be rapidly detected and treated. Automatic detection systems are essential for controlling pandemic. Molecular techniques medical imaging scans among most effective approaches detecting COVID-19. Although these crucial pandemic, they have certain limitations. This study proposes an hybrid approach based on genomic image processing (GIP)...

<title>Abstract</title> Breast cancer, with its high incidence and mortality globally, necessitates early prediction of local distant recurrence toimprove treatment outcomes. This study develops validates predictive models for breast cancer metastasisusing Recurrence-Free Survival Analysis (RFS) machine learning techniques. We merged datasets from the MolecularTaxonomy Cancer International Consortium (METABRIC), Memorial Sloan Kettering Center (MSK), DukeUniversity, SEER program, creating a...

Objective. Our main objective is to demonstrate that compact high radiance gallium nitride displays can be used with conventional virtual reality optics stimulate an optogenetic retina. Hence, we aim introduce a non-invasive approach restore vision for people conditions such as retinitis pigmentosa where there remaining viable communication link between the retina and visual cortex. Approach. We design implement headset using high-density µLED matrix, Raspberry Pi, microcontroller from NXP...

The field of retinal prosthesis has been steadily developing over the last two decades. Despite many obstacles, clinical trials for electronic approaches are in progress and already demonstrating some success. Optogenetic/optoelectronic may prove to have even greater capabilities. Although resolutions now moving beyond recognition simple shapes, it will nevertheless be poor compared normal vision. If we define aim return mobility natural scene patient, is important maximize useful visual...

Retina degenerative disorders represent the primary cause of blindness in UK and developed world. In particular, Age Related Macular Degeneration (AMD) Pigmentosa (RP) diseases are interest to this study. We have therefore created new image processing algorithms for enhancing visual scenes them. paper we present three novel enhancement techniques aimed at remaining information patients suffering from retina dystrophies. Currently, only effective way test technology is undergo testing on...

Abstract Hepatitis C virus (HCV) is a major global health concern, affecting millions of individuals worldwide. While existing literature predominantly focuses on disease classification using clinical data, there exists critical research gap concerning HCV genotyping based genomic sequences. Accurate essential for patient management and treatment decisions. the neural models excel at capturing complex patterns, they still face challenges, such as data scarcity, that exist lot in...

In this paper we present a novel scene retargeting technique to reduce the visual while maintaining size of key features. The algorithm is scalable implementation onto portable devices, and thus, has potential for augmented reality systems provide support those with tunnel vision. We therefore test efficacy our on shrinking into remaining field view patients. Simple spatial compression scenes makes objects appear further away. have developed an which removes low importance information,...

The objective of this research is to build a “Whole Slide Images” classification system using Convolutional Neural Network (CNN). This capable classifying Thyroid tumors into three types: Follicular adenoma, follicular carcinoma, and papillary carcinoma. Furthermore, the cascaded CNN technique additionally employed classify classified carcinoma four subclasses: variant, well-differentiated Poorly-differentiated Results proposed architecture showed effective in whole slide images with an...

Coronavirus (CoV) disease 2019 (COVID-19) is a severe pandemic affecting millions worldwide. Due to its rapid evolution, researchers have been working on developing diagnostic approaches suppress spread. This study presents an effective automated approach based genomic image processing (GIP) techniques rapidly detect COVID-19, among other human CoV diseases, with high acceptable accuracy. The GIP technique was applied as follows: first, graphical mapping were used convert the genome...

Patients with low vision have reduced visual acuity and a significant loss of contrast sensitivity resulting in gross blurring the scene over area their field view. This paper describes robust approach for edge enhancement impairments patients, based on simplifying to remove unnecessary textures then enhance edges simplified image. The effectiveness this scheme was demonstrated pilot study composed three patients suffering from macular degeneration. They succeeded identify most objects...

Abstract Salient object detection is an increasingly popular topic in the computer vision field, particularly for images with complex backgrounds and diverse parts. Background information essential factor detecting salient objects. This paper suggests a robust effective methodology detection. method involves two main stages. The first stage to produce saliency map based on dense sparse reconstruction of image regions using refined background dictionary. dictionary uses boundary conductivity...

Portable image processing systems require algorithms which reduce the power consumption while maintaining video rate operation. This paper describes how splitting data stream into multiple pipelines can in contrast to traditional spatial (pipeline) parallel technique. Real-time system functions (Sobel filters and anisotropic diffusion) were implemented show principle of Our results that partitioning sections gives increasing benefits with shorter times, up 45% drop consumption.

One of the most serious problems that faces human nowadays is gait disturbances as result neurodegenerative diseases (NDD). Neurodegenerative such Parkinson's disease (PD), Amyotrophic Lateral Sclerosis (ALS), Huntington Disease (HD) identified dynamic loss neurons in brain. Therefore, analysis can yield a significant approach for early diagnosis and determine treatment plan with generation new era computerized medical systems analyzing diseases. The present study explores improvement...

The DNA motif discovery is an important step to study gene function. A refers a short similar repeated pattern of nucleotides that has biological meaning. In this paper, bio-inspired algorithm called Grey Wolf Optimizer technique for finding (GWOMF) presented and evaluated on six synthetic datasets. Experimental results show the GWOMF more efficient than state-of-art methods with comparable computational time. Results confirmed robustness new demonstrate its value as tool average success rate 86.6%.