Artificial intelligence for breast cancer analysis: Trends & directions
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …
cancer can significantly improve the lives of millions of women across the globe. Given …
Deep learning for medical image-based cancer diagnosis
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …
diagnosis. To help readers better understand the current research status and ideas, this …
Connected-UNets: a deep learning architecture for breast mass segmentation
Breast cancer analysis implies that radiologists inspect mammograms to detect suspicious
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …
breast lesions and identify mass tumors. Artificial intelligence techniques offer automatic …
Boosting breast cancer detection using convolutional neural network
SA Alanazi, MM Kamruzzaman… - Journal of …, 2021 - Wiley Online Library
Breast cancer forms in breast cells and is considered as a very common type of cancer in
women. Breast cancer is also a very life‐threatening disease of women after lung cancer. A …
women. Breast cancer is also a very life‐threatening disease of women after lung cancer. A …
YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms
Background and objective Both mass detection and segmentation in digital mammograms
play a crucial role in early breast cancer detection and treatment. Furthermore, clinical …
play a crucial role in early breast cancer detection and treatment. Furthermore, clinical …
Intelligent hybrid deep learning model for breast cancer detection
Breast cancer (BC) is a type of tumor that develops in the breast cells and is one of the most
common cancers in women. Women are also at risk from BC, the second most life …
common cancers in women. Women are also at risk from BC, the second most life …
ME-CCNN: Multi-encoded images and a cascade convolutional neural network for breast tumor segmentation and recognition
R Ranjbarzadeh, S Jafarzadeh Ghoushchi… - Artificial Intelligence …, 2023 - Springer
Breast tumor segmentation and recognition from mammograms play a key role in healthcare
and treatment services. As different tumors in mammography have dissimilar densities …
and treatment services. As different tumors in mammography have dissimilar densities …
[HTML][HTML] Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
Recent work has shown that label-efficient few-shot learning through self-supervision can
achieve promising medical image segmentation results. However, few-shot segmentation …
achieve promising medical image segmentation results. However, few-shot segmentation …
MRFE-CNN: Multi-route feature extraction model for breast tumor segmentation in Mammograms using a convolutional neural network
R Ranjbarzadeh, N Tataei Sarshar… - Annals of Operations …, 2023 - Springer
Breast cancer is cancer that develops from the breast tissue and has been recognized as
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
one of the most dangerous and deadly diseases that is the second leading cause of cancer …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …