Systematic review of computing approaches for breast cancer detection based computer aided diagnosis using mammogram images
DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Artificial …, 2021 - Taylor & Francis
Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …
Deep learning-based metaheuristic weighted k-nearest neighbor algorithm for the severity classification of breast cancer
Objective The most widespread and intrusive cancer type among women is breast cancer.
Globally, this type of cancer causes more mortality among women, next to lung cancer. This …
Globally, this type of cancer causes more mortality among women, next to lung cancer. This …
Tetromino pattern based accurate EEG emotion classification model
Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …
In silico molecular docking and dynamic simulation of eugenol compounds against breast cancer
Breast cancer is one of the most severe problems, and it is the primary cause of cancer-
related death in females worldwide. The adverse effects and therapeutic resistance …
related death in females worldwide. The adverse effects and therapeutic resistance …
Internet of medical things embedding deep learning with data augmentation for mammogram density classification
T Sadad, AR Khan, A Hussain, U Tariq… - Microscopy …, 2021 - Wiley Online Library
Females are approximately half of the total population worldwide, and most of them are
victims of breast cancer (BC). Computer‐aided diagnosis (CAD) frameworks can help …
victims of breast cancer (BC). Computer‐aided diagnosis (CAD) frameworks can help …
[HTML][HTML] Novel texture feature descriptors based on multi-fractal analysis and lbp for classifying breast density in mammograms
H Li, R Mukundan, S Boyd - Journal of Imaging, 2021 - mdpi.com
This paper investigates the usefulness of multi-fractal analysis and local binary patterns
(LBP) as texture descriptors for classifying mammogram images into different breast density …
(LBP) as texture descriptors for classifying mammogram images into different breast density …
A new local pooling approach for convolutional neural network: local binary pattern
The pooling layer used in CNN models aims to reduce the resolution of image/feature maps
while retaining their distinctive information, reducing computation time and enabling deeper …
while retaining their distinctive information, reducing computation time and enabling deeper …
Comparative analysis of segment anything model and u-net for breast tumor detection in ultrasound and mammography images
In this study, the main objective is to develop an algorithm capable of identifying and
delineating tumor regions in breast ultrasound (BUS) and mammographic images. The …
delineating tumor regions in breast ultrasound (BUS) and mammographic images. The …
Cross vision transformer with enhanced Growth Optimizer for breast cancer detection in IoMT environment
The recent advances in artificial intelligence modern approaches can play vital roles in the
Internet of Medical Things (IoMT). Automatic diagnosis is one of the most important topics in …
Internet of Medical Things (IoMT). Automatic diagnosis is one of the most important topics in …
Breast density classification in mammogram images
V Vyshnavi, D Vijayan… - 2021 Seventh International …, 2021 - ieeexplore.ieee.org
Breast cancer is the common type of cancer in the world, which is most common among
women. It is found that there is a correlation between the breast cancer and breast density …
women. It is found that there is a correlation between the breast cancer and breast density …