Medical Image Denoising Techniques against Hazardous Noises: An IQA Metrics Based Comparative Analysis

Boby, Shakil Mahmud; Sharmin, Shaela

doi:10.5815/ijigsp.2021.02.03

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…Medical imaging is one of the most essential and often the only source of information for patient diagnosis and treatment planning/course. This information is used by virtually all physicians, surgeons, and other medical personnel [21][22].…”

Section: Current Issuesmentioning

confidence: 99%

The Efficient and Secure Digital Management System for Radiologists

Iavich,

Sharvadze

2024

Advances in Transdisciplinary Engineering

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This article describes the authors’ research on a unified digital management system for the clinic. The system is focused on the use of radiologists and medical imaging. The goal of the research is to develop a unified, secure, and efficient management system for the clinic. The system uses a single-window principle, fully integrates all clinic management systems into one environment, and fully digitizes them. Due to the scattered processes across different areas, the current clinical management systems do not have all the necessary structures, processes, data, and systems integrated into a single electronic environment. This article describes one of the medical visualization modules of the new research-based medical facility management software, which will be integrated into a unified hospital management system. The system has a Web-based interface and is compatible with a variety of mobile devices. The system provides security features such as password policies and user role management. The system works in a secure network environment. Experiments conducted in a test environment have revealed that the new system improves the efficiency of delivering medical services and reduces the time needed to deliver a medical service. The significance lies in the potential to transform clinic management, optimize clinical processes, and ultimately enhance the quality of patient care. The findings have relevance not only for the medical community but also for technology developers and policymakers aiming to advance healthcare systems.

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Section: Current Issuesmentioning

confidence: 99%

The Efficient and Secure Digital Management System for Radiologists

Iavich,

Sharvadze

2024

Advances in Transdisciplinary Engineering

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“…In the pre-processing part, there are several filters used for noise removal, like; Median, Wiener, Anisotropic Diffusion filter, Non Local Means, etc. (15,16) Using an estimate of the necessary noise-free signal, the Wiener filter is frequently used in this to reduce the amount of distortion in a scan. It uses a statistical method.…”

Section: Theoretical Aspect Of Techniquesmentioning

confidence: 99%

Development of a New Algorithm for Classifying Cerebral Tumours Using MRI Images

Pancholi

Modi

Chitaliya

2023

Salud, Ciencia y Tecnología

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Los científicos sanitarios han determinado que las imágenes de resonancia magnética han sido muy beneficiosas en los últimos tiempos para la investigación del reconocimiento y la identificación precoz de enfermedades cerebrales. Las principales etapas primarias en el análisis de las imágenes de resonancia magnética del cerebro son el preprocesamiento de imágenes, la segmentación, la extracción de características y la clasificación. Entre los procesos cruciales que pueden evaluar lo bien que se pueden clasificar las imágenes de resonancia magnética del cerebro y, en última instancia, la enfermedad que indicarán, se encuentran la extracción de características y la segmentación. En este artículo se describen métodos por etapas. En la primera etapa (etapa de preprocesamiento) se utilizan diferentes filtros, como la mediana, wiener, anisotrópico, medios no locales, así como filtros combinados. En la parte de preprocesamiento, los filtros wiener y anisotrópico combinados dan el mejor resultado. En la segunda etapa (etapa de segmentación), la técnica de umbralización múltiple - algoritmo de búsqueda de cuco utilizado utilizando diferentes funciones objetivas; como; ostu, kapur entropía, tsallis entropía y propuso. En el método propuesto de la etapa de segmentación utilizado cuckoo algoritmo de búsqueda utilizando ostu combinado y tsallis entropía como función objetivo. En la tercera etapa (extracción de características), transformada wavelet discreta utilizada y en la cuarta etapa (clasificación) máquina de vectores soporte utilizado. En cada etapa se comparan los resultados utilizando diferentes parámetros y se obtienen los mejores resultados utilizando el método propuesto.

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Brain Tumor Detection with Ensemble of Convolutional Neural Networks and Vision Transformer

Yurdakul,

TAŞDEMİR

2023

2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)

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Medical Image Denoising Techniques against Hazardous Noises: An IQA Metrics Based Comparative Analysis

Cited by 5 publications

References 32 publications

The Efficient and Secure Digital Management System for Radiologists

The Efficient and Secure Digital Management System for Radiologists

Development of a New Algorithm for Classifying Cerebral Tumours Using MRI Images

Brain Tumor Detection with Ensemble of Convolutional Neural Networks and Vision Transformer

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