ArticleBiomedical optics express2021
Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging.
Article in Biomedical optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A standardized workflow for precision liver resection: systematic review of integrated 3D visualization, indocyanine green fluorescence, and augmented reality navigation.Journal of robotic surgery · 2026Pooled it
- Niche preclinical and clinical applications of photoacoustic imaging with endogenous contrast.Photoacoustics · 2023Review
- Full-view in vivo skin and blood vessels profile segmentation in photoacoustic imaging based on deep learning.Photoacoustics · 2022Article
- Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: introduction to the feature issue.Biomedical optics express · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
The adaptive matched filter (AMF) is a method widely used in spectral unmixing to classify different tissue chromophores in photoacoustic images. However, a threshold needs to be applied to the AMF detection image to distinguish the desired tissue chromophores from the background. In this study, we propose an automatic threshold selection (ATS) algorithm capable of differentiating a target from the background, based on the features of the AMF detection image. The mean difference between the estimated thickness, using the ATS algorithm, and the known values was 0.17 SD (0.24) mm for the phantom inclusions and -0.05 SD (0.21) mm for the tissue samples of malignant melanoma. The evaluation shows that the thickness and the width of the phantom inclusions and the tumors can be estimated using AMF in an automatic way after applying the ATS algorithm.
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Registered trials
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