A review of automatic mass detection and segmentation in mammographic images
A Oliver, J Freixenet, J Marti, E Perez, J Pont… - Medical image …, 2010 - Elsevier
The aim of this paper is to review existing approaches to the automatic detection and
segmentation of masses in mammographic images, highlighting the key-points and main …
segmentation of masses in mammographic images, highlighting the key-points and main …
Artificial intelligence methods for the diagnosis of breast cancer by image processing: a review
F Sadoughi, Z Kazemy, F Hamedan, L Owji… - … Cancer: Targets and …, 2018 - Taylor & Francis
Breast cancer is the most common cancer among women around the world. Despite
enormous medical progress, breast cancer has still remained the second leading cause of …
enormous medical progress, breast cancer has still remained the second leading cause of …
Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c‐means clustering and support vector machine …
Purpose: The amount of fibroglandular tissue content in the breast as estimated
mammographically, commonly referred to as breast percent density (PD%), is one of the …
mammographically, commonly referred to as breast percent density (PD%), is one of the …
Multi-view mammographic density classification by dilated and attention-guided residual learning
Breast density is widely adopted to reflect the likelihood of early breast cancer development.
Existing methods of mammographic density classification either require steps of manual …
Existing methods of mammographic density classification either require steps of manual …
PCA-PNN and PCA-SVM based CAD systems for breast density classification
Early prediction of breast density is clinically significant as there is an association between
the risk of breast cancer development and breast density. In the present work, the …
the risk of breast cancer development and breast density. In the present work, the …
Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment
Purpose: Mammographic percent density (PD%) is known to be a strong risk factor for breast
cancer. Recent studies also suggest that parenchymal texture features, which are more …
cancer. Recent studies also suggest that parenchymal texture features, which are more …
Mammographic classification based on XGBoost and DCNN with multi features
R Song, T Li, Y Wang - IEEE Access, 2020 - ieeexplore.ieee.org
The classification of benign and malignant masses in mammograms by Computer-Aided
Diagnosis (CAD) is one of the most difficult and important tasks in the development of CAD …
Diagnosis (CAD) is one of the most difficult and important tasks in the development of CAD …
Automated assessment of breast tissue density in digital mammograms
TS Subashini, V Ramalingam, S Palanivel - Computer Vision and Image …, 2010 - Elsevier
Mammographic density is known to be an important indicator of breast cancer risk.
Classification of mammographic density based on statistical features has been investigated …
Classification of mammographic density based on statistical features has been investigated …
Classification of breast density categories based on SE-Attention neural networks
J Deng, Y Ma, D Li, J Zhao, Y Liu, H Zhang - Computer Methods and …, 2020 - Elsevier
Background and objective: Breast density (BD) is an independent predictor of breast cancer
risk factor. The automatic classification of BD has yet to resolve. In this paper, we propose an …
risk factor. The automatic classification of BD has yet to resolve. In this paper, we propose an …
Review of recent advances in segmentation of the breast boundary and the pectoral muscle in mammograms
This paper presents a review of recent advances in the development of methods for
segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless …
segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless …