[HTML][HTML] Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review
The relatively recent reintroduction of deep learning has been a revolutionary force in the
interpretation of diagnostic imaging studies. However, the technology used to acquire those …
interpretation of diagnostic imaging studies. However, the technology used to acquire those …
A data set and deep learning algorithm for the detection of masses and architectural distortions in digital breast tomosynthesis images
Importance Breast cancer screening is among the most common radiological tasks, with
more than 39 million examinations performed each year. While it has been among the most …
more than 39 million examinations performed each year. While it has been among the most …
A deep learning model using data augmentation for detection of architectural distortion in whole and patches of images
ON Oyelade, AE Ezugwu - Biomedical Signal Processing and Control, 2021 - Elsevier
Breast cancer is now widely known to be the second most lethal disease among women.
Computer-aided detection (CAD) systems, deep learning (DL) in particular, have continued …
Computer-aided detection (CAD) systems, deep learning (DL) in particular, have continued …
Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review
Background Recent advancements in computing power and state-of-the-art algorithms have
helped in more accessible and accurate diagnosis of numerous diseases. In addition, the …
helped in more accessible and accurate diagnosis of numerous diseases. In addition, the …
A comparative performance study of random‐grid model for hyperparameters selection in detection of abnormalities in digital breast images
ON Oyelade, AE Ezugwu - Concurrency and Computation …, 2022 - Wiley Online Library
Deep learning models have been widely reported to have achieved significant performance
in image processing and classification tasks. They have mainly been harnessed and applied …
in image processing and classification tasks. They have mainly been harnessed and applied …
Atypical architectural distortion detection in digital breast tomosynthesis: a computer-aided detection model with adaptive receptive field
Y Li, Z He, J Pan, W Zeng, J Liu, Z Zeng… - Physics in Medicine …, 2023 - iopscience.iop.org
Objective. In digital breast tomosynthesis (DBT), architectural distortion (AD) is a breast
lesion that is difficult to detect. Compared with typical ADs, which have radial patterns …
lesion that is difficult to detect. Compared with typical ADs, which have radial patterns …
CAPNet: Context attention pyramid network for computer-aided detection of microcalcification clusters in digital breast tomosynthesis
J Wang, H Sun, K Jiang, W Cao, S Chen, J Zhu… - Computer Methods and …, 2023 - Elsevier
Background and objective Computer-aided detection (CADe) of microcalcification clusters
(MCs) in digital breast tomosynthesis (DBT) is crucial in the early diagnosis of breast cancer …
(MCs) in digital breast tomosynthesis (DBT) is crucial in the early diagnosis of breast cancer …
Dual-branch convolutional neural network based on ultrasound imaging in the early prediction of neoadjuvant chemotherapy response in patients with locally …
J Xie, H Shi, C Du, X Song, J Wei, Q Dong… - Frontiers in …, 2022 - frontiersin.org
The early prediction of a patient's response to neoadjuvant chemotherapy (NAC) in breast
cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel …
cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel …
Diagnosis of architectural distortion on digital breast tomosynthesis using radiomics and deep learning
Purpose To implement two Artificial Intelligence (AI) methods, radiomics and deep learning,
to build diagnostic models for patients presenting with architectural distortion on Digital …
to build diagnostic models for patients presenting with architectural distortion on Digital …
Architectural distortion detection based on superior–inferior directional context and anatomic prior knowledge in digital breast tomosynthesis
Background In 2020, breast cancer becomes the most leading diagnosed cancer all over the
world. The burden is increasing in the prevention and treatment of breast cancer. Accurately …
world. The burden is increasing in the prevention and treatment of breast cancer. Accurately …