Breast cancer diagnosis in digital breast tomosynthesis: effects of training sample size on multi-stage transfer learning using deep neural nets
In this paper, we developed a deep convolutional neural network (CNN) for the classification
of malignant and benign masses in digital breast tomosynthesis (DBT) using a multi-stage …
of malignant and benign masses in digital breast tomosynthesis (DBT) using a multi-stage …
Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification
X Li, G Qin, Q He, L Sun, H Zeng, Z He, W Chen… - European …, 2020 - Springer
Objective To evaluate the impact of utilizing digital breast tomosynthesis (DBT) or/and full-
field digital mammography (FFDM), and different transfer learning strategies on deep …
field digital mammography (FFDM), and different transfer learning strategies on deep …
Latent feature representation with 3-D multi-view deep convolutional neural network for bilateral analysis in digital breast tomosynthesis
In clinical studies of breast cancer, masses appear as asymmetric densities between the left
and the right breasts, which show different breast tissue structures. For classifying breast …
and the right breasts, which show different breast tissue structures. For classifying breast …
DBT Masses Automatic Segmentation Using U‐Net Neural Networks
X Lai, W Yang, R Li - Computational and mathematical methods …, 2020 - Wiley Online Library
To improve the automatic segmentation accuracy of breast masses in digital breast
tomosynthesis (DBT) images, we propose a DBT mass automatic segmentation algorithm by …
tomosynthesis (DBT) images, we propose a DBT mass automatic segmentation algorithm by …
ICADx: interpretable computer aided diagnosis of breast masses
In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate
interpretability for classifying breast masses. Recently, a deep learning technology has been …
interpretability for classifying breast masses. Recently, a deep learning technology has been …
Latent feature representation with depth directional long-term recurrent learning for breast masses in digital breast tomosynthesis
Abstract Characterization of masses in computer-aided detection systems for digital breast
tomosynthesis (DBT) is an important step to reduce false positive (FP) rates. To effectively …
tomosynthesis (DBT) is an important step to reduce false positive (FP) rates. To effectively …
Automated segmentation of mass regions in DBT images using a dilated DCNN approach
J Ye, W Yang, J Wang, X Xu, L Li, C Xie… - Computational …, 2022 - Wiley Online Library
To overcome the limitations of conventional breast screening methods based on digital
mammography, a quasi‐3D imaging technique, digital breast tomosynthesis (DBT) has been …
mammography, a quasi‐3D imaging technique, digital breast tomosynthesis (DBT) has been …
A collection input based support tensor machine for lesion malignancy classification in digital breast tomosynthesis
Digital breast tomosynthesis (DBT) with improved lesion conspicuity and characterization
has been adopted in screening practice. DBT-based diagnosis strongly depends on …
has been adopted in screening practice. DBT-based diagnosis strongly depends on …
Improving mass detection using combined feature representations from projection views and reconstructed volume of DBT and boosting based classification with …
In digital breast tomosynthesis (DBT), image characteristics of projection views and
reconstructed volume are different and both have the advantage of detecting breast masses …
reconstructed volume are different and both have the advantage of detecting breast masses …
Detection of masses in digital breast tomosynthesis using complementary information of simulated projection
Purpose: The purpose of this study is to develop a computer‐aided detection system that
combines the detection results in 3D digital breast tomosynthesis (DBT) volume and 2D …
combines the detection results in 3D digital breast tomosynthesis (DBT) volume and 2D …