Discrimination of the Skin Microcirculatory Status Using Photoacoustic Technique and Long Short-term Memory Network
DOI:
https://doi.org/10.3991/ijoe.v18i01.27415Keywords:
Photoacoustic imaging, microcirculatory changes, temporal features, long short-term memoryAbstract
Measuring oxygen in blood with a standard imaging method is challenging. Most of the conventional imaging systems presented outcomes of microcirculatory change measurement as signals of complex forms. This leads to analytical insufficiency due to the complicated and visually unnoticeable features of the signals. For that reason, there is a great need to explore the use of photoacoustic (PA) method and deep learning technique for the task. This work presents the use of a deep network containing long short-term memory (LSTM) units for temporal features extraction and classification of skin microcirculatory status. The model was trained using a limited number of PA signals. One way ANOVA test was used to evaluate changes in the PA signals collected under different experiment condition. The results showed a strong statistical significance between the means of two groups (ρ < 0.05). The mean ± standard deviation (SD) final validation accuracies of the trained model is given by 95.60 ± 0.47 % with inclusion of augmented data, which showed better performance than the case without the augmentation method. The results of the testing set showed a considerably good classification accuracy, specificity, and sensitivity given by 97.6 %, 100 %, and 83.3%. The future of this work includes improvement of the network architecture to include more convolutional layers for searching patterns in the features extracted.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Hui Ling Chua, Audrey Huong
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.