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A systematic review on breast cancer detection using deep learning techniques
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 …
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
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 …
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
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 …
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 …
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
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 …
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 …
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 …
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
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 …
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
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 …
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
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 …
early stage, a computer-aided diagnosis (CAD) system can be designed using X-ray …