Open AccessAutomatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging
Author(s) -
Azin Khodaverdi,
Tobias Erlöv,
Jenny Hult,
Nina Reistad,
Ágnes Pekár-Lukacs,
John Albinsson,
Aboma Merdasa,
Rafi Sheikh,
Malin Malmsjö,
Magnus Cinthio
Publication year - 2021
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.422170
Subject(s) - imaging phantom , chromophore , photoacoustic imaging in biomedicine , computer science , multispectral image , filter (signal processing) , image processing , optics , materials science , artificial intelligence , algorithm , biomedical engineering , computer vision , pattern recognition (psychology) , image (mathematics) , physics , medicine , quantum mechanics
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.