AIMC Topic: Mammography

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Deep learning-driven prediction in healthcare systems: Applying advanced CNNs for enhanced breast cancer detection.

Computers in biology and medicine Feb 27, 2025
The mortality risk associated with breast cancer is experiencing an exponential rise, underscoring the critical importance of early detection. It is the primary cause of mortality among women under 50 and ranks as the second deadliest disease globall...
Early Detection of Cancer Mammography Breast Neoplasms Humans Middle Aged Deep Learning Neural Networks, Computer Female
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An enhanced denoising system for mammogram images using deep transformer model with fusion of local and global features.

Scientific reports Feb 24, 2025
Image denoising is a critical problem in low-level computer vision, where the aim is to reconstruct a clean, noise-free image from a noisy input, such as a mammogram image. In recent years, deep learning, particularly convolutional neural networks (C...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Mammography Signal-To-Noise Ratio Female Breast Neoplasms Deep Learning
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Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.

Physics in medicine and biology Feb 18, 2025
State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammograms with pectoral muscle (PM) included. This study investigated whether excluding PM during training/fine-tuning improves the model's BCR discriminatio...
Risk Assessment Deep Learning Mammography Breast Neoplasms Middle Aged Calibration Risk Pectoralis Muscles Humans Female
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Deep transfer learning based hierarchical CAD system designs for SFM images.

Journal of medical engineering & technology Feb 14, 2025
Present work involves rigorous experimentation for classification of mammographic masses by employing four deep transfer learning models using hierarchical framework. Experimental work is carried on 518 SFM images of DDSM dataset with 208, 150 and 16...
Breast Neoplasms Humans Deep Learning Female Mammography
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An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Scientific reports Feb 9, 2025
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...
Biomarkers, Tumor Middle Aged Deep Learning Convolutional Neural Networks ROC Curve Mammography Receptors, Progesterone Female Receptor, ErbB-2 Adult Humans Receptors, Estrogen Breast Neoplasms Neural Networks, Computer
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[Artificial intelligence in breast imaging : Hopes and challenges].

Radiologie (Heidelberg, Germany) Feb 6, 2025
CLINICAL/METHODICAL ISSUE: Artificial intelligence (AI) is being increasingly integrated into clinical practice. However, the specific benefits are still unclear to many users.
Female Breast Neoplasms Mammography Humans Artificial Intelligence
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You get the best of both worlds? Integrating deep learning and traditional machine learning for breast cancer risk prediction.

Computers in biology and medicine Feb 5, 2025
Breast Cancer is the most commonly diagnosed cancer worldwide. While screening mammography diminishes the burden of this disease, it has some flaws related to the presence of false negatives. Adapting screening to each woman's needs could help overco...
Case-Control Studies Deep Learning Early Detection of Cancer Mammography Breast Neoplasms Middle Aged Risk Assessment Aged Adult Humans Machine Learning Female
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Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.

Scientific reports Feb 5, 2025
Employing two standard mammography views is crucial for radiologists, providing comprehensive insights for reliable clinical evaluations. This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast ...
Humans Algorithms Female Mammography Radiographic Image Interpretation, Computer-Assisted Breast Neoplasms Deep Learning
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Breast cancer classification based on hybrid CNN with LSTM model.

Scientific reports Feb 5, 2025
Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. The speed-up process of detection and classification is crucial for effective cancer treatment. Medical image analysis methods and computer-aided diag...
Mammography Neural Networks, Computer Breast Neoplasms Humans Algorithms Diagnosis, Computer-Assisted Female Deep Learning
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Integrating Eye Tracking With Grouped Fusion Networks for Semantic Segmentation on Mammogram Images.

IEEE transactions on medical imaging Feb 4, 2025
Medical image segmentation has seen great progress in recent years, largely due to the development of deep neural networks. However, unlike in computer vision, high-quality clinical data is relatively scarce, and the annotation process is often a bur...
Algorithms Female Breast Neoplasms Humans Neural Networks, Computer Mammography Eye-Tracking Technology Breast Deep Learning Semantics Image Processing, Computer-Assisted
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