[HTML][HTML] A review of explainable deep learning cancer detection models in medical imaging
Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
Systematic review of computing approaches for breast cancer detection based computer aided diagnosis using mammogram images
DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Artificial …, 2021 - Taylor & Francis
Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …
[HTML][HTML] Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review
A Gastounioti, S Desai, VS Ahluwalia, EF Conant… - Breast Cancer …, 2022 - Springer
Background Improved breast cancer risk assessment models are needed to enable
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …
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 …
A systematic survey of deep learning in breast cancer
In recent years, we witnessed a speeding development of deep learning in computer vision
fields like categorization, detection, and semantic segmentation. Within several years after …
fields like categorization, detection, and semantic segmentation. Within several years after …
[HTML][HTML] 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 …
[HTML][HTML] Breast cancer detection: Shallow convolutional neural network against deep convolutional neural networks based approach
Introduction: Of all the cancers that afflict women, breast cancer (BC) has the second-highest
mortality rate, and it is also believed to be the primary cause of the high death rate. Breast …
mortality rate, and it is also believed to be the primary cause of the high death rate. Breast …
[HTML][HTML] The role of deep learning in advancing breast cancer detection using different imaging modalities: A systematic review
Simple Summary Breast cancer is the most common cancer, which resulted in the death of
700,000 people around the world in 2020. Various imaging modalities have been utilized to …
700,000 people around the world in 2020. Various imaging modalities have been utilized to …
[HTML][HTML] Shape-based breast lesion classification using digital tomosynthesis images: The role of explainable artificial intelligence
Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
Breast cancer classification using FCN and beta wavelet autoencoder
HN AlEisa, W Touiti, A Ali ALHussan… - Computational …, 2022 - Wiley Online Library
In this paper, a new classification approach of breast cancer based on Fully Convolutional
Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful …
Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful …