AIMC Topic: Ultrasonography, Mammary
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US-based Radiomics Analysis of Different Machine Learning Models for Differentiating Benign and Malignant BI-RADS 4A Breast Lesions.
Academic radiology
Aug 26, 2024
RATIONALE AND OBJECTIVES: To investigate and authenticate the effectiveness of various radiomics models in distinguishing between benign and malignant BI-RADS 4A lesions.
Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy.
Academic radiology
Aug 24, 2024
RATIONALE AND OBJECTIVES: This study aims to explore the feasibility of the deep learning radiomics nomogram (DLRN) for predicting tumor status and axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy (NAC) in patients with breast can...
Computer-Aided Classification of Breast Lesions Based on US RF Time Series Using a Novel Machine Learning Approach.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Aug 14, 2024
OBJECTIVES: One of the most promising adjuncts for screening breast cancer is ultrasound (US) radio-frequency (RF) time series. It has the superiority of not requiring any supplementary equipment over other methods. This research aimed to propound a ...
Advancing breast ultrasound diagnostics through hybrid deep learning models.
Computers in biology and medicine
Aug 13, 2024
Today, doctors rely heavily on medical imaging to identify abnormalities. Proper classification of these abnormalities enables them to take informed actions, leading to early diagnosis and treatment. This paper introduces the "EfficientKNN" model, a ...
Comparative Analysis of the Diagnostic Value of S-Detect Technology in Different Planes Versus the BI-RADS Classification for Breast Lesions.
Academic radiology
Aug 12, 2024
RATIONALE AND OBJECTIVES: S-Detect, a deep learning-based Computer-Aided Detection system, is recognized as an important tool for diagnosing breast lesions using ultrasound imaging. However, it may exhibit inconsistent findings across multiple imagin...
Deep learning-based computer-aided detection of ultrasound in breast cancer diagnosis: A systematic review and meta-analysis.
Clinical radiology
Aug 8, 2024
PURPOSE: The aim of this meta-analysis was to assess the diagnostic performance of deep learning (DL) and ultrasound in breast cancer diagnosis. Additionally, we categorized the included studies into two subgroups: B-mode ultrasound diagnostic subgro...
Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.
Academic radiology
Aug 5, 2024
RATIONALE AND OBJECTIVES: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established ...
Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer.
BMC medical imaging
Jul 26, 2024
BACKGROUND: The purpose of this study is to develop and validate the potential value of the deep learning radiomics nomogram (DLRN) based on ultrasound to differentiate mass mastitis (MM) and invasive breast cancer (IBC).
A deep learning-based method for the detection and segmentation of breast masses in ultrasound images.
Physics in medicine and biology
Jul 26, 2024
Automated detection and segmentation of breast masses in ultrasound images are critical for breast cancer diagnosis, but remain challenging due to limited image quality and complex breast tissues. This study aims to develop a deep learning-based meth...
Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jul 25, 2024
OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the breast tissue. In a few cases, erroneous diagnosis of breast cancer by specialists and unnecessary biopsies can lead to various negative consequences. In ...
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