A bottom-up review of image analysis methods for suspicious region detection in mammograms
Breast cancer is one of the most common death causes amongst women all over the world.
Early detection of breast cancer plays a critical role in increasing the survival rate. Various …
Early detection of breast cancer plays a critical role in increasing the survival rate. Various …
Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms
Objective: Mammogram-based automatic breast cancer detection has a primary role in
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
An efficient segmentation and classification system in medical images using intuitionist possibilistic fuzzy C-mean clustering and fuzzy SVM algorithm
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with
breast cancer. More effort is needed to assess the role of these viruses in the detection and …
breast cancer. More effort is needed to assess the role of these viruses in the detection and …
Multi-category intuitionistic fuzzy twin support vector machines with an application to plant leaf recognition
The intuitionistic fuzzy twin support vector machine for multi-categorization is developed in
this study, which incorporates both structural and empirical risk concepts. In this method …
this study, which incorporates both structural and empirical risk concepts. In this method …
An effective detection and classification of road damages using hybrid deep learning framework
D Deepa, A Sivasangari - Multimedia Tools and Applications, 2023 - Springer
The monitoring of road surfaces is a critical thing in transport infrastructure management.
The manual reporting process increases the processing delay and causes challenges in …
The manual reporting process increases the processing delay and causes challenges in …
Fast and efficient method for optical coherence tomography images classification using deep learning approach
RK Ara, A Matiolański, A Dziech, R Baran, P Domin… - Sensors, 2022 - mdpi.com
The use of optical coherence tomography (OCT) in medical diagnostics is now common. The
growing amount of data leads us to propose an automated support system for medical staff …
growing amount of data leads us to propose an automated support system for medical staff …
Early diagnosis model of Alzheimer's disease based on sparse logistic regression
R Xiao, X Cui, H Qiao, X Zheng, Y Zhang - Multimedia Tools and …, 2021 - Springer
Accurate classification of Alzheimer's Disease (AD) and its prodromal stage, ie, mild
cognitive impairment (MCI) are critical for the effective treatment of AD. However, compared …
cognitive impairment (MCI) are critical for the effective treatment of AD. However, compared …
[PDF][PDF] Mammography Images Segmentation via Fuzzy C-mean and K-mean
Breast Cancer is one of the common and dangerous among women at the age of forty, so it
is better for woman to have mammography testing as a significant step for the early detection …
is better for woman to have mammography testing as a significant step for the early detection …
Pectoral muscle removal using entropy fuzzy clustering and RCM-CNN based mammography classification
One of the most prominent cancers in women is breast cancer. This research study focuses
on the development of an entropy-based fuzzy clustering and classification using Region …
on the development of an entropy-based fuzzy clustering and classification using Region …
A Weight Possibilistic Fuzzy C‐Means Clustering Algorithm
J Chen, H Zhang, D Pi, M Kantardzic… - Scientific …, 2021 - Wiley Online Library
Fuzzy C‐means (FCM) is an important clustering algorithm with broad applications such as
retail market data analysis, network monitoring, web usage mining, and stock market …
retail market data analysis, network monitoring, web usage mining, and stock market …