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A systematic literature review of breast cancer diagnosis using machine intelligence techniques
Breast cancer is one of the most common diseases in women; it can have long-term
implications and can even be fatal. However, early detection, achieved through recent …
implications and can even be fatal. However, early detection, achieved through recent …
Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet
S Samudrala, CK Mohan - Multimedia Tools and Applications, 2024 - Springer
For early detection of cancer tumors, the semantic segmentation based technique is
proposed because the existing numerous methods fail while classifying due to accuracy and …
proposed because the existing numerous methods fail while classifying due to accuracy and …
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 …
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 …
Deep learning empowered breast cancer diagnosis: Advancements in detection and classification
Recent advancements in AI, driven by big data technologies, have reshaped various
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …
industries, with a strong focus on data-driven approaches. This has resulted in remarkable …
Computer-aided breast cancer diagnosis: Comparative analysis of breast imaging modalities and mammogram repositories
The accurate assessment or diagnosis of breast cancer depends on image acquisition and
image analysis and interpretation. The expert radiologist makes image interpretation, and …
image analysis and interpretation. The expert radiologist makes image interpretation, and …
A novel hybrid K-means and GMM machine learning model for breast cancer detection
Breast cancer is the second leading cause of death among a large number of women
worldwide. It may be challenging for radiologists to diagnose and treat breast cancer …
worldwide. It may be challenging for radiologists to diagnose and treat breast cancer …
Deep integrated pipeline of segmentation guided classification of breast cancer from ultrasound images
Breast cancer has become a symbol of tremendous concern in the modern world, as it is one
of the major causes of cancer mortality worldwide. In this regard, breast ultrasonography …
of the major causes of cancer mortality worldwide. In this regard, breast ultrasonography …
Improving breast cancer detection and diagnosis through semantic segmentation using the Unet3+ deep learning framework
We present an analysis and evaluation of breast cancer detection and diagnosis using
segmentation models. We used an advanced semantic segmentation method and a deep …
segmentation models. We used an advanced semantic segmentation method and a deep …
[HTML][HTML] Novel insights in spatial epidemiology utilizing explainable AI (XAI) and remote sensing
The COVID-19 pandemic has affected many aspects of human life around the world, due to
its tremendous outcomes on public health and socio-economic activities. Policy makers …
its tremendous outcomes on public health and socio-economic activities. Policy makers …