A flexible AI pipeline for medical imaging in a radiology workflow

Lucia Antunez; Julio Castellanos; Gonzalo Raposo; Camila Murga M.D.

doi:10.1117/12.2606146

10 December 2021 A flexible AI pipeline for medical imaging in a radiology workflow

Lucia Antunez, Julio Castellanos, Gonzalo Raposo, Camila Murga M.D.

Proceedings Volume 12088, 17th International Symposium on Medical Information Processing and Analysis; 1208816 (2021) https://doi.org/10.1117/12.2606146
Event: Seventeenth International Symposium on Medical Information Processing and Analysis, 2021, Campinas, Brazil

Abstract

Medical imaging analysis is an effective technique and process for visualizing the human body’s interior to diagnose, monitor, and treat medical conditions. Artificial Intelligence (AI) brings new opportunities for improvement, with multiple applications in all levels of the radiology workflow. This paper presents a solution that leverages state-of-the-art models and architectures to assemble a modular pipeline for detection, segmentation, measurement, and scoring, that builds up to an optimized clinical report for medical imaging analysis and diagnosis. The proposed approach is designed to be flexible and tailor-made to an end facility’s needs and data, helping the radiologist’s effectiveness.

Citation Download Citation

Lucia Antunez, Julio Castellanos, Gonzalo Raposo, and Camila Murga M.D. "A flexible AI pipeline for medical imaging in a radiology workflow", Proc. SPIE 12088, 17th International Symposium on Medical Information Processing and Analysis, 1208816 (10 December 2021); https://doi.org/10.1117/12.2606146

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