Automated breast cancer detection in mammography using ensemble classifier and feature weighting algorithms
Breast cancer exhibits one of the highest incidence and mortality rates among all cancers
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
affecting women. The early detection of breast cancer reduces mortality and is crucial for …
[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …
Breast cancer diagnosis using an efficient CAD system based on multiple classifiers
Breast cancer is one of the major health issues across the world. In this study, a new
computer-aided detection (CAD) system is introduced. First, the mammogram images were …
computer-aided detection (CAD) system is introduced. First, the mammogram images were …
A novel breast cancer detection architecture based on a CNN-CBR system for mammogram classification
L Bouzar-Benlabiod, K Harrar, L Yamoun… - Computers in biology …, 2023 - Elsevier
This paper presents a novel framework for breast cancer detection using mammogram
images. The proposed solution aims to output an explainable classification from a …
images. The proposed solution aims to output an explainable classification from a …
Mammography image-based diagnosis of breast cancer using machine learning: a pilot study
A tumor is an abnormal tissue classified as either benign or malignant. A breast tumor is one
of the most common tumors in women. Radiologists use mammograms to identify a breast …
of the most common tumors in women. Radiologists use mammograms to identify a breast …
Automatic detection of abnormal mammograms in mammographic images
CC Jen, SS Yu - Expert Systems with Applications, 2015 - Elsevier
This paper proposes a detection method for abnormal mammograms in mammographic
datasets based on the novel abnormality detection classifier (ADC) by extracting a few of …
datasets based on the novel abnormality detection classifier (ADC) by extracting a few of …
Automated mammogram breast cancer detection using the optimized combination of convolutional and recurrent neural network
RS Patil, N Biradar - Evolutionary intelligence, 2021 - Springer
The objective of this study is to frame mammogram breast detection model using the
optimized hybrid classifier. Image pre-processing, tumor segmentation, feature extraction …
optimized hybrid classifier. Image pre-processing, tumor segmentation, feature extraction …
Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review
Breast cancer is the most common form of cancer among women worldwide. Early detection
of breast cancer can increase treatment options and patients' survivability. Mammography is …
of breast cancer can increase treatment options and patients' survivability. Mammography is …
An approach for automatic lesion detection in mammograms
KU Sheba, S Gladston Raj - Cogent Engineering, 2018 - Taylor & Francis
Early stage breast cancer detection can reduce death rates in long term. Mammography is
the current standard screening tool available for breast cancer detection, but it is found to …
the current standard screening tool available for breast cancer detection, but it is found to …
An effective ensemble machine learning approach to classify breast cancer based on feature selection and lesion segmentation using preprocessed mammograms
Simple Summary The screening of breast cancer in its earlier stages can play a crucial role
in minimizing mortality rate by enabling clinicians to administer timely treatments and …
in minimizing mortality rate by enabling clinicians to administer timely treatments and …