Abstract: The present approach relates to providing image quality feedback to personnel (e.g., a technician) acquiring non-invasive images 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 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.

Abstract: The present approach relates to providing image quality feedback to personnel (e.g., a technician) acquiring non-invasive images 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 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.

Abstract: Embodiments described herein provide an image analytics platform that follows a microservice-based architecture. The platform provides a set of algorithms implemented as microservices to design knowledge-based models. The image analytics platform is deployed in the cloud for management and storage of images. In order to facilitate the design, composition and integration of the algorithms, a web application facilitates design of the knowledge models by the use of directed graphs. The web application allows physicians to design specific knowledge models and share with others; developers can easily add and test new image processing algorithms; and physicians can design and test different algorithms and evaluate selected results in a more efficient way.