Document Type
Conference Proceeding
Publication Date
4-1-2020
Abstract
© 2020 IEEE. Myocardial infarction (MI) is a scientific term that refers to heart attack. In this study, we infer highly relevant second harmonic generation (SHG) cues from collagen fibers exhibiting highly non-centrosymmetric assembly together with two-photon excited cellular autofluorescence in infarcted mouse heart to quantitatively probe fibrosis, especially targeted at an early stage after MI. We present a robust one-shot machine learning algorithm that enables determination of 2D assembly of collagen with high spatial resolution along with its structural arrangement in heart tissues post - MI with spectral specificity and sensitivity. Detection, evaluation, and precise quantification of fibrosis extent at early stage would guide one to develop treatment therapies that may prevent further progression and determine heart transplant needs for patient survival.
Publication Source (Journal or Book title)
Proceedings - International Symposium on Biomedical Imaging
First Page
839
Last Page
843
Recommended Citation
Liu, Q., Mukhopadhyay, S., Bastidas Rodriguez, M., Fu, X., Sahu, S., Burk, D., & Gartia, M. (2020). A One-Shot Learning Framework for Assessment of Fibrillar Collagen from Second Harmonic Generation Images of an Infarcted Myocardium. Proceedings - International Symposium on Biomedical Imaging, 2020-April, 839-843. https://doi.org/10.1109/ISBI45749.2020.9098444