Real-time 3D echocardiography (RT3DE) has already been shown to be an accurate tool for left ventricular (LV) volume assessment. However, LV border detection in RT3DE remains a time-consuming task jeopardizing the application of this modality in routine practice. We have recently developed a 3D automated segmentation framework (BEAS) able to capture the LV morphology in real-time. The goal of this study was to assess the accuracy of this approach in extracting volumetric parameters in a clinical setting. 24 RT3DE exams were acquired in a group of healthy volunteers (# = 5) and diseased patients (# = 19), with LV volume/function within a range typically measured in a clinical setting. End-diastolic and end-systolic volumes (EDV, ESV) were manually contoured by 3 expert sonographers from which the stroke volume and ejection fraction (SV, EF) were calculated. The values extracted with BEAS were compared to the average of the 3 experts measurements using correlation and Bland-Altman statistics. Linear regression analysis showed a strong correlation between the automated algorithm and the reference values (R = 0.963, 0.947, 0.944 and 0.853 for EDV, ESV, SV and EF respectively). Bland-Altman analysis revealed a bias (limits of agreement) of 2.59 (−25.39, 30.57) ml, −2.11 (−24.91, 20.69) ml, 4.70 (12.93, 22.34) ml and 3.45 (−8.96, 15.87) %, for EDV, ESV, SV and EF respectively. Total analysis time using BEAS was 30.7 ± 7.5 s. BEAS allows for a fast and accurate quantification of 3D cardiac volumes and global function with minimal user input. It may therefore contribute to the integration of 3D echocardiography in routine clinical practice.