Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review
NIR Yassin, S Omran, EMF El Houby… - Computer methods and …, 2018 - Elsevier
Background and objective The high incidence of breast cancer in women has increased
significantly in the recent years. Physician experience of diagnosing and detecting breast …
significantly in the recent years. Physician experience of diagnosing and detecting breast …
[HTML][HTML] A curated mammography data set for use in computer-aided detection and diagnosis research
Published research results are difficult to replicate due to the lack of a standard evaluation
data set in the area of decision support systems in mammography; most computer-aided …
data set in the area of decision support systems in mammography; most computer-aided …
Detecting and classifying lesions in mammograms with deep learning
In the last two decades, Computer Aided Detection (CAD) systems were developed to help
radiologists analyse screening mammograms, however benefits of current CAD …
radiologists analyse screening mammograms, however benefits of current CAD …
YOLO based breast masses detection and classification in full-field digital mammograms
Abstract Background and Objective With the recent development in deep learning since
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …
Applying data-driven imaging biomarker in mammography for breast cancer screening: preliminary study
We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised
learning (DIB; an imaging biomarker derived from large-scale medical image data with deep …
learning (DIB; an imaging biomarker derived from large-scale medical image data with deep …
[HTML][HTML] A survey of convolutional neural network in breast cancer
Aims A large number of clinical trials have proved that if breast cancer is diagnosed at an
early stage, it could give patients more treatment options and improve the treatment effect …
early stage, it could give patients more treatment options and improve the treatment effect …
A review of computer aided detection in mammography
J Katzen, K Dodelzon - Clinical imaging, 2018 - Elsevier
Breast screening with mammography is widely recognized as the most effective method of
detecting early breast cancer and has consistently demonstrated a 20–40% decrease in …
detecting early breast cancer and has consistently demonstrated a 20–40% decrease in …
A cloud-based predictive model for the detection of breast cancer
Invasive cancer is the biggest cause of death worldwide, especially among women. Early
cancer detection is vital to health. Early identification of breast cancer improves prognosis …
cancer detection is vital to health. Early identification of breast cancer improves prognosis …
Impact of computer-aided detection systems on radiologist accuracy with digital mammography
EB Cole, Z Zhang, HS Marques… - American Journal of …, 2014 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study was to assess the impact of computer-aided
detection (CAD) systems on the performance of radiologists with digital mammograms …
detection (CAD) systems on the performance of radiologists with digital mammograms …