Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
Mammography, or breast X-ray imaging, is the most widely used imaging modality to detect
cancer and other breast diseases. Recent studies have shown that deep learning-based …
cancer and other breast diseases. Recent studies have shown that deep learning-based …
An online mammography database with biopsy confirmed types
Breast carcinoma is the second largest cancer in the world among women. Early detection of
breast cancer has been shown to increase the survival rate, thereby significantly increasing …
breast cancer has been shown to increase the survival rate, thereby significantly increasing …
ADMANI: Annotated digital mammograms and associated non-image datasets
HML Frazer, JSN Tang, MS Elliott… - Radiology: Artificial …, 2022 - pubs.rsna.org
ADMANI: Annotated Digital Mammograms and Associated Non-Image Datasets | Radiology:
Artificial Intelligence RSNA "skipMainNavigation" closeDrawerMenuopenDrawerMenu Home …
Artificial Intelligence RSNA "skipMainNavigation" closeDrawerMenuopenDrawerMenu Home …
Symmetry-based regularization in deep breast cancer screening
Breast cancer is the most common and lethal form of cancer in women. Recent efforts have
focused on develo** accurate neural network-based computer-aided diagnosis systems …
focused on develo** accurate neural network-based computer-aided diagnosis systems …
MOB-CBAM: A dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms
Abstract Background and objective Deep Learning models have emerged as a significant
tool in generating efficient solutions for complex problems including cancer detection, as …
tool in generating efficient solutions for complex problems including cancer detection, as …
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses
To generate evidence regarding the safety and efficacy of artificial intelligence (AI) enabled
medical devices, AI models need to be evaluated on a diverse population of patient cases …
medical devices, AI models need to be evaluated on a diverse population of patient cases …
Breast cancer: toward an accurate breast tumor detection model in mammography using transfer learning techniques
Female breast cancer has now surpassed lung cancer as the most common form of cancer
globally. Although several methods exist for breast cancer detection and diagnosis …
globally. Although several methods exist for breast cancer detection and diagnosis …
Physical imaging parameter variation drives domain shift
Statistical learning algorithms strongly rely on an oversimplified assumption for optimal
performance, that is, source (training) and target (testing) data are independent and …
performance, that is, source (training) and target (testing) data are independent and …
A comparison of techniques for class imbalance in deep learning classification of breast cancer
Tools based on deep learning models have been created in recent years to aid radiologists
in the diagnosis of breast cancer from mammograms. However, the datasets used to train …
in the diagnosis of breast cancer from mammograms. However, the datasets used to train …