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Medical image analysis using convolutional neural networks: a review
The science of solving clinical problems by analyzing images generated in clinical practice
is known as medical image analysis. The aim is to extract information in an affective and …
is known as medical image analysis. The aim is to extract information in an affective and …
Image thresholding approaches for medical image segmentation-short literature review
Medical image analysis is an invaluable tool in medicine. Different imaging modalities
provide an effective means for map** images that can feed machine and deep learning …
provide an effective means for map** images that can feed machine and deep learning …
An extended machine learning technique for polycystic ovary syndrome detection using ovary ultrasound image
Polycystic ovary syndrome (PCOS) is the most prevalent endocrinological abnormality and
one of the primary causes of anovulatory infertility in women globally. The detection of …
one of the primary causes of anovulatory infertility in women globally. The detection of …
Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation
The ant colony optimization (ACO) is the most exceptionally fundamental swarm-based
solver for realizing discrete problems. In order to make it also suitable for solving continuous …
solver for realizing discrete problems. In order to make it also suitable for solving continuous …
Image segmentation using multilevel thresholding: a research review
Image segmentation is a basic problem in computer vision and various image processing
applications. Over the years, commonly used image segmentation has become quite …
applications. Over the years, commonly used image segmentation has become quite …
A hybrid DenseNet121-UNet model for brain tumor segmentation from MR Images
Several techniques are used to detect brain tumors in the medical research field; however,
Magnetic Resonance Imaging (MRI) is still the most effective technique used by experts …
Magnetic Resonance Imaging (MRI) is still the most effective technique used by experts …
Multi-threshold image segmentation using a multi-strategy shuffled frog lea** algorithm
Medical image segmentation, which is a complex and fundamental step in medical image
processing, can help doctors make more precise decisions on patient diagnosis. Although …
processing, can help doctors make more precise decisions on patient diagnosis. Although …
Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation
L Liu, D Zhao, F Yu, AA Heidari, J Ru, H Chen… - Computers in Biology …, 2021 - Elsevier
Breast cancer is one of the most dangerous diseases for women's health, and it is imperative
to provide the necessary diagnostic assistance for it. The medical image processing …
to provide the necessary diagnostic assistance for it. The medical image processing …
Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
Introduction: Alzheimer's Disease (AD) is a degenerative brain disorder characterized by
cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the …
cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the …
Brain image segmentation based on FCM clustering algorithm and rough set
In this paper, a new image segmentation method is proposed by combining the FCM
clustering algorithm with a rough set theory. First, the attribute value table is constructed …
clustering algorithm with a rough set theory. First, the attribute value table is constructed …