The present approach relates to providing image quality feedback to personnel (e.g., a technician) acquiring non-invasive images 300 in real-time or near real-time. By way of example, the proposed approach may automatically assess the quality of images in real-time by evaluating the images 300 for the presence or absence of non-conformities using processor-implemented, rule-based algorithms running partly or completely in parallel to one another. The proposed approach improves the image analysis pipeline by efficiently providing notification of and/or discarding low-quality or unsuitable images or exams after they are taken, such as in within seconds or minutes.
