Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms
Objective: Mammogram-based automatic breast cancer detection has a primary role in
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
Machine learning based Breast Cancer screening: trends, challenges, and opportunities
Although breast cancer (BC) deaths have decreased over time, it remains the second
leading cause of cancer-related deaths among women. With the technical advancement of …
leading cause of cancer-related deaths among women. With the technical advancement of …
Shape-based breast lesion classification using digital tomosynthesis images: The role of explainable artificial intelligence
Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
New horizons: artificial intelligence for digital breast tomosynthesis
The use of digital breast tomosynthesis (DBT) in breast cancer screening has become
widely accepted, facilitating increased cancer detection and lower recall rates compared …
widely accepted, facilitating increased cancer detection and lower recall rates compared …
Diagnosis system for cancer disease using a single setting approach
HK Bhuyan, A Vijayaraj, V Ravi - Multimedia Tools and Applications, 2023 - Springer
This paper addresses the diagnosis system of cancer disease using a single setting
framework. Most of the radiologists and image specialists are identifying the disease in …
framework. Most of the radiologists and image specialists are identifying the disease in …
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 …
Identification and diagnosis of mammographic malignant architectural distortion using a deep learning based mask regional convolutional neural network
Y Liu, Y Tong, Y Wan, Z Xia, G Yao, X Shang… - Frontiers in …, 2023 - frontiersin.org
Background Architectural distortion (AD) is a common imaging manifestation of breast
cancer, but is also seen in benign lesions. This study aimed to construct deep learning …
cancer, but is also seen in benign lesions. This study aimed to construct deep learning …
Deep-AutoMO: Deep automated multiobjective neural network for trustworthy lesion malignancy diagnosis in the early stage via digital breast tomosynthesis
Breast cancer is the most prevalent cancer in women, and early diagnosis of malignant
lesions is crucial for developing treatment plans. Digital breast tomosynthesis (DBT) has …
lesions is crucial for developing treatment plans. Digital breast tomosynthesis (DBT) has …
Convolutional neural network-based phantom image scoring for mammography quality control
VM Sundell, T Mäkelä, AM Vitikainen… - BMC Medical Imaging, 2022 - Springer
Background Visual evaluation of phantom images is an important, but time-consuming part
of mammography quality control (QC). Consistent scoring of phantom images over the …
of mammography quality control (QC). Consistent scoring of phantom images over the …
Classifying Breast Tumors in Digital Tomosynthesis by Combining Image Quality-Aware Features and Tumor Texture Descriptors
Digital breast tomosynthesis (DBT) is a 3D breast cancer screening technique that can
overcome the limitations of standard 2D digital mammography. However, DBT images often …
overcome the limitations of standard 2D digital mammography. However, DBT images often …