Brain tumor segmentation and classification by improved binomial thresholding and multi-features selection
A malignant tumor in brain is detected using images from Magnetic Resonance scanners.
Malignancy detection in brain and separation of its tissues from normal brain cells allows to …
Malignancy detection in brain and separation of its tissues from normal brain cells allows to …
DWT-PCA image fusion technique to improve segmentation accuracy in brain tumor analysis
Because of its high clinical significance and varied modalities; magnetic resonance (MR)
imaging procedures are widely adopted in medical discipline to record the abnormalities …
imaging procedures are widely adopted in medical discipline to record the abnormalities …
Brain tumor segmentation utilizing thresholding and K-means clustering
R Khilkhal, M Ismael - 2022 Muthanna International Conference …, 2022 - ieeexplore.ieee.org
The segmentation of brain tumors utilizing magnetic resonance imaging (MRI) is a critical
step in medical image processing. This results from the valuable information obtained from …
step in medical image processing. This results from the valuable information obtained from …
Medical imaging and its objective quality assessment: an introduction
With the rise in research on applications of medical image processing, the evaluation of
parameters and techniques required for measurement of medical image quality is the need …
parameters and techniques required for measurement of medical image quality is the need …
Computer-aided diagnosis of melanoma: a review of existing knowledge and strategies
Computer-aided diagnosis (CAD) systems are the best alternative for immediate disclosure
and diagnosis of skin diseases. Such systems comprise several image processing …
and diagnosis of skin diseases. Such systems comprise several image processing …
Medical image segmentation using fruit fly optimization and density peaks clustering
H Zhu, H He, J Xu, Q Fang… - … mathematical methods in …, 2018 - Wiley Online Library
In this paper, we propose a novel algorithm for medical image segmentation, which
combines the density peaks clustering (DPC) with the fruit fly optimization algorithm, and it …
combines the density peaks clustering (DPC) with the fruit fly optimization algorithm, and it …
A study on segmentation of leukocyte image with Shannon's entropy
In recent years, a considerable number of approaches have been proposed by the
researchers to evaluate infectious diseases by examining the digital images of peripheral …
researchers to evaluate infectious diseases by examining the digital images of peripheral …
[PDF][PDF] Edge enhancement based on an active contour model for the segmentation of brain tumors in MRI images
MR Ismael - ECTI Transactions on Electrical Engineering …, 2021 - academia.edu
Tumor segmentation is one of the most important tasks in brain image analysis due to the
significant information contained in the tumor region. Therefore, many methods have been …
significant information contained in the tumor region. Therefore, many methods have been …
Big Data Summarization Using Modified Fuzzy Clustering Algorithm, Semantic Feature, and Data Compression Approach
SG Kolte, JW Bakal - Applied Machine Learning for Smart Data …, 2019 - taylorfrancis.com
The ever-evolving improvements in processing and storage capacity of gadgets demand
effective data-mining procedures to obtain the correct and important data. Data …
effective data-mining procedures to obtain the correct and important data. Data …