A systematic review on breast cancer detection using deep learning techniques

K Rautela, D Kumar, V Kumar - Archives of Computational Methods in …, 2022 - Springer
Breast cancer is a common health problem in women, with one out of eight women dying
from breast cancer. Many women ignore the need for breast cancer diagnosis as the …

Fuzzy C-means and region growing based classification of tumor from mammograms using hybrid texture feature

T Sadad, A Munir, T Saba, A Hussain - Journal of computational science, 2018 - Elsevier
Identifying abnormality using breast mammography is a challenging task for radiologists due
to its nature. A more consistent and precise imaging based CAD system plays a vital role in …

An improved scheme for digital mammogram classification using weighted chaotic salp swarm algorithm-based kernel extreme learning machine

F Mohanty, S Rup, B Dash, B Majhi, MNS Swamy - Applied Soft Computing, 2020 - Elsevier
Over the past years, the surge in the necessity for early detection and diagnosis of breast
cancer has resulted in many innovative research directions. According to the World Health …

Detection and classification of microcalcification from digital mammograms with firefly algorithm, extreme learning machine and non‐linear regression models: A …

SR Sannasi Chakravarthy… - International Journal of …, 2020 - Wiley Online Library
In this study, abnormalities in medical images are analysed using three classifiers, and the
results are compared. Breast cancer remains a major public health problem among women …

Two-way threshold-based intelligent water drops feature selection algorithm for accurate detection of breast cancer

DJ Kalita, VP Singh, V Kumar - Soft Computing, 2022 - Springer
Breast cancer is one of the common reasons for deaths of women over the globe. It has
been found that a Computer-Aided Diagnosis (CAD) system can be designed using X-ray …

Optimal weighted hybrid pattern for content based medical image retrieval using modified spider monkey optimization

N Darapureddy, N Karatapu… - International Journal of …, 2021 - Wiley Online Library
The current approaches for image retrieval are more concentrating on numerous image
features. Texture, shape, spatial information, and color are the fundamental features to deal …

Detection and classification of breast cancer from digital mammograms using hybrid extreme learning machine classifier

JG Melekoodappattu, PS Subbian… - International Journal of …, 2021 - Wiley Online Library
Breast imaging technique called mammography has gained bigger attention among the
researchers for the diagnosis of breast malignancy in the woman. Mammogram screening is …

Hybridized deep convolutional neural network and fuzzy support vector machines for breast cancer detection

IS Oyetade, JO Ayeni, AO Ogunde, BO Oguntunde… - SN Computer …, 2022 - Springer
A cancerous development that originates from breast tissue is known as breast cancer, and
it is reported to be the leading cause of women death globally. Previous researches have …

Restoration and enhancement of breast ultrasound images using extended complex diffusion based unsharp masking

A Kumar, S Srivastava - … , Part H: Journal of Engineering in …, 2022 - journals.sagepub.com
Ultrasound is a well-known imaging modality for the interpretation of breast cancer. It is
playing very important role for breast cancer detection that are missed by mammograms …

Detection of breast cancer through mammogram using wavelet-based LBP features and IWD feature selection technique

DJ Kalita, VP Singh, V Kumar - SN Computer Science, 2022 - Springer
Breast cancer is as one of the common reasons of deaths in women. To detect this cancer in
early stage, a computer-aided diagnosis (CAD) system can be designed using X-ray …