Rapid lipid-laden plaque identification in intravascular OCT imaging based on time-series deep learning

Jose J. Rico-Jimenez; Javier A. Jo

doi:10.1117/12.2608303

7 March 2022 Rapid lipid-laden plaque identification in intravascular OCT imaging based on time-series deep learning

Jose J. Rico-Jimenez, Javier A. Jo

Proceedings Volume PC11936, Diagnostic and Therapeutic Applications of Light in Cardiology 2022; PC119360D (2022) https://doi.org/10.1117/12.2608303
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Coronary heart disease has the highest rate of death and morbidity in the Western world. Lipid-laden plaques containing a necrotic core may eventually rupture causing heart attack and stroke. Intravascular Optical Coherence Tomography (IV-OCT) imaging has been used for plaque assessment. However, the IV-OCT images are visually interpreted, which is burdensome and require highly trained physicians. This study aims to provide high throughput lipid-laden plaque identification that can assist in vivo imaging by offering faster screening and guided decision-making during percutaneous coronary interventions. An A-line wise classification methodology based on time-series deep learning is presented to fulfill this aim.

Conference Presentation

Citation Download Citation

Jose J. Rico-Jimenez and Javier A. Jo "Rapid lipid-laden plaque identification in intravascular OCT imaging based on time-series deep learning", Proc. SPIE PC11936, Diagnostic and Therapeutic Applications of Light in Cardiology 2022, PC119360D (7 March 2022); https://doi.org/10.1117/12.2608303

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