Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm
In the last decade, there has been a significant increase in medical cases involving brain
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
tumors. Brain tumor is the tenth most common type of tumor, affecting millions of people …
[HTML][HTML] Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm
In the present era, human brain tumor is the extremist dangerous and devil to the human
being that leads to certain death. Furthermore, the brain tumor arises more complexity of …
being that leads to certain death. Furthermore, the brain tumor arises more complexity of …
A review on recent progress in machine learning and deep learning methods for cancer classification on gene expression data
Data-driven model with predictive ability are important to be used in medical and healthcare.
However, the most challenging task in predictive modeling is to construct a prediction model …
However, the most challenging task in predictive modeling is to construct a prediction model …
Computational Intelligence and Metaheuristic Techniques for Brain Tumor Detection through IoMT‐Enabled MRI Devices
The brain tumor is the 22nd most common cancer worldwide, with 1.8% of new cancers. It is
likely the most severe ailment that necessitates early discovery and treatment, and it …
likely the most severe ailment that necessitates early discovery and treatment, and it …
RVM-MR image brain tumour classification using novel statistical feature extractor
Abstract Diagnosis of Brain Tumor is a prominent area of research in biomedical image
processing to renovate the radiological machine with acquired magnetic resonance (MR) …
processing to renovate the radiological machine with acquired magnetic resonance (MR) …
A brain tumor segmentation and detection technique based on birch and marker watershed
H Moussaoui, N El Akkad, M Benslimane - SN Computer Science, 2023 - Springer
Today, image segmentation plays a vital role in many crucial areas. This paper will cover the
important role that image segmentation plays in medical imaging issues. Image …
important role that image segmentation plays in medical imaging issues. Image …
A review on the techniques of brain tumor: Segmentation, feature extraction and classification
G Yogalakshmi, BS Rani - 2020 11th International Conference …, 2020 - ieeexplore.ieee.org
Tumor has become a thread and widely spread all over the world in today's life. In Scientific
term when body cells does not divide in proper fashion or sequence to form new cell it may …
term when body cells does not divide in proper fashion or sequence to form new cell it may …
Improving Minimum Cross‐Entropy Thresholding for Segmentation of Infected Foregrounds in Medical Images Based on Mean Filters Approaches
WAH Jumiawi, A El-Zaart - Contrast Media & Molecular Imaging, 2022 - Wiley Online Library
Mean‐based thresholding methods are among the most popular techniques that are used
for images segmentation. Thresholding is a fundamental process for many applications …
for images segmentation. Thresholding is a fundamental process for many applications …
Improvement in the between-class variance based on lognormal distribution for accurate image segmentation
WAH Jumiawi, A El-Zaart - Entropy, 2022 - mdpi.com
There are various distributions of image histograms where regions form symmetrically or
asymmetrically based on the frequency of the intensity levels inside the image. In pure …
asymmetrically based on the frequency of the intensity levels inside the image. In pure …
Brain tumor classification from MRI images and calculation of tumor area
M Pareek, CK Jha, S Mukherjee - Soft Computing: Theories and …, 2020 - Springer
Medical imaging plays an important role to generate images of mankind for clinical and
medical research. In this paper, we are focused on the detection of brain tumor using MRI …
medical research. In this paper, we are focused on the detection of brain tumor using MRI …