Descriptor: Cardiac Multi-view EchO Dataset (CAMEO)

The clinical diagnosis of cardiovascular diseases from echocardiographic images requires experts to monitor different heart views. However, current datasets lack complete views of the heart for clinical diagnosis. This article introduces a novel publicly available dataset for multi-view echocardiogram classification: the cardiac multi-view echo dataset (CAMEO). The CAMEO dataset comprises high-quality cardiac ultrasound images collected from 9 standard echocardiographic views, including the apical, parasternal long axis, parasternal short axis, and subcostal views. Unlike publicly available echocardiographic datasets, which typically focus on a subset of views or lack detailed annotations, the CAMEO dataset provides a complete set of standard cardiac views and fine-grained details within each view. The dataset offers diverse demographics of patients, comprehensive annotations, and expert-labeled diagnostic categories, ensuring its applicability to the development and benchmarking of algorithms for classification tasks, cardiac disease detection, and motion analysis. CAMEO dataset addresses existing gaps in echocardiographic datasets by offering extensive imaging quality, consistent protocols, and multi-view coverage, enabling researchers to evaluate deep learning models in realistic clinical scenarios. Potential applications span cardiology research, automated diagnosis, and developing novel image processing techniques for echocardiograms. By providing this resource, we aim to accelerate advancements in echocardiographic image analysis, improving diagnostic accuracy and patient care.