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Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
Radiomics in breast cancer: Current advances and future directions
Breast cancer is a common disease that causes great health concerns to women worldwide.
During the diagnosis and treatment of breast cancer, medical imaging plays an essential …
During the diagnosis and treatment of breast cancer, medical imaging plays an essential …
A hierarchical graph V-Net with semi-supervised pre-training for histological image based breast Cancer classification
Numerous patch-based methods have recently been proposed for histological image based
breast cancer classification. However, their performance could be highly affected by ignoring …
breast cancer classification. However, their performance could be highly affected by ignoring …
[HTML][HTML] Edge of discovery: Enhancing breast tumor MRI analysis with boundary-driven deep learning
Manually segmenting breast lesion images poses a labor-intensive and expensive
undertaking for radiologists. Therefore, the adoption of an automated diagnostic approach …
undertaking for radiologists. Therefore, the adoption of an automated diagnostic approach …
The Smart Performance Comparison of AI-based Breast Cancer Detection Models
The smart performance comparison of AI-based breast cancer detection models is an
important research topic in the healthcare industry. It is used to compare and evaluate …
important research topic in the healthcare industry. It is used to compare and evaluate …
Prototype learning guided hybrid network for breast tumor segmentation in dce-mri
Automated breast tumor segmentation on the basis of dynamic contrast-enhancement
magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice …
magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice …
Modality-specific information disentanglement from multi-parametric MRI for breast tumor segmentation and computer-aided diagnosis
Breast cancer is becoming a significant global health challenge, with millions of fatalities
annually. Magnetic Resonance Imaging (MRI) can provide various sequences for …
annually. Magnetic Resonance Imaging (MRI) can provide various sequences for …
Evaluating magnetic seed localization in targeted axillary dissection for node-positive early breast cancer patients receiving neoadjuvant systemic therapy: a …
Background/Objectives: De-escalation of axillary surgery is made possible by
advancements in both neoadjuvant systemic therapy (NST) and in localisation technology …
advancements in both neoadjuvant systemic therapy (NST) and in localisation technology …
Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Using a Longitudinally Aware Segmentation Network
“Just Accepted” papers have undergone full peer review and have been accepted for
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …
Breast fibroglandular tissue segmentation for automated BPE quantification with iterative cycle-consistent semi-supervised learning
Background Parenchymal Enhancement (BPE) quantification in Dynamic Contrast-
Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast …
Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast …