This study focuses on gathering a comprehensive dataset of conventional ultrasound images to support the development of advanced training models in medical imaging. With over 3,000 participants, the study aims to create a robust and diverse collection of images representing a wide range of anatomical regions and clinical conditions. The dataset will serve as a foundational resource for improving diagnostic accuracy and enhancing machine learning applications in ultrasound analysis.
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