AIMC Topic: Ultrasonography
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MM-UKAN++: A Novel Kolmogorov-Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Apr 22, 2025
Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (ROIs) in US images is essential for enhancing the efficiency of clinical and robot-assisted diagnosis...
Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Apr 22, 2025
Resolving arterial flows is essential for understanding cardiovascular pathologies, improving diagnosis, and monitoring patient condition. Ultrasound contrast imaging uses microbubbles to enhance the scattering of the blood pool, allowing for real-ti...
Combining Ultrasound Imaging and Molecular Testing in a Multimodal Deep Learning Model for Risk Stratification of Indeterminate Thyroid Nodules.
Thyroid : official journal of the American Thyroid Association
Apr 21, 2025
Indeterminate cytology (Bethesda III and IV) represents 15-30% of biopsied thyroid nodules and require additional diagnostic testing. Molecular testing (MT) is a commonly used diagnostic tool that evaluatesmalignancy risk through next generation seq...
Development and Validation an AI Model to Improve the Diagnosis of Deep Infiltrating Endometriosis for Junior Sonologists.
Ultrasound in medicine & biology
Apr 17, 2025
OBJECTIVE: This study aims to develop and validate an artificial intelligence (AI) model based on ultrasound (US) videos and images to improve the performance of junior sonologists in detecting deep infiltrating endometriosis (DE).
Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.
Technology in cancer research & treatment
Apr 17, 2025
IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in predicting preoperative axillary lymph node metastasis using primary breast cancer and lymph node features derived from contrast-enhanced mammography...
An Ultrasound-based Machine Learning Model for Predicting Tumor-Infiltrating Lymphocytes in Breast Cancer.
Technology in cancer research & treatment
Apr 17, 2025
IntroductionTumor-infiltrating lymphocytes (TILs) are key indicators of immune response and prognosis in breast cancer (BC). Accurate prediction of TIL levels is essential for guiding personalized treatment strategies. This study aimed to develop and...
Deep Learning-Based Medical Ultrasound Image and Video Segmentation Methods: Overview, Frontiers, and Challenges.
Sensors (Basel, Switzerland)
Apr 8, 2025
The intricate imaging structures, artifacts, and noise present in ultrasound images and videos pose significant challenges for accurate segmentation. Deep learning has recently emerged as a prominent field, playing a crucial role in medical image pro...
Prediction of Seronegative Hashimoto's thyroiditis using machine learning models based on ultrasound radiomics: a multicenter study.
BMC immunology
Apr 7, 2025
BACKGROUND: Seronegative Hashimoto's thyroiditis is often underdiagnosed due to the lack of antibody markers. Combining ultrasound radiomics with machine learning offers potential for early detection in patients with normal thyroid function.
FreqYOLO: A uterine disease detection network based on local and global frequency feature learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 4, 2025
Leiomyomas (LM) and adenomyosis (AM) are common gynecological diseases with high incidence rates and an increasing trend of affecting younger women. Accurate detection and differentiation of LM and AM in ultrasound images are crucial for selecting ap...
Method of Forearm Muscles 3D Modeling Using Robotic Ultrasound Scanning.
Sensors (Basel, Switzerland)
Apr 4, 2025
The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabilitation, and biomechanical research. This study presents a novel methodology for constructing volumetric models of forearm muscles based on three-dim...
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