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Updated: Oct 22, 2025
Ovarian Cancer Detection Using Photoacoustic Flow Cytometry
Published on: January 17, 2020
Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic
Azin Khodaverdi1, Tobias Erlöv1, Jenny Hult2
1Department of Biomedical Engineering, Faculty of Engineering, Lund University, SE-221 00 Lund, Sweden.
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.
