Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging

Azin Khodaverdi; Tobias Erlöv; Jenny Hult; Nina Reistad; Agnes Pekar-Lukacs; John Albinsson; Aboma Merdasa; Rafi Sheikh; Malin Malmsjö; Magnus Cinthio

doi:10.1364/BOE.422170

Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging

Biomed Opt Express. 2021 Jun 4;12(7):3836-3850. doi: 10.1364/BOE.422170. eCollection 2021 Jul 1.

Authors

Affiliations

¹ Department of Biomedical Engineering, Faculty of Engineering, Lund University, SE-221 00 Lund, Sweden.
² Department of Clinical Sciences Lund, Skane University Hospital, Lund University, SE-221 00 Lund, Sweden.
³ Department of Physics, Faculty of Engineering, Lund University, SE-221 00 Lund, Sweden.
⁴ Department of Oncology and Pathology, Skane University Hospital, 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.