Automatic Threshold Selection Algorithm to Distinguish a Tissue Chromophore from the Background in Photoacoustic Imaging

Overview

Journal Biomed Opt Express

Specialty Radiology

Date 2021 Aug 30

PMID 34457383

Citations 3

Authors

Azin Khodaverdi

Tobias Erlov

Jenny Hult

Nina Reistad

Agnes Pekar-Lukacs

John Albinsson

Aboma Merdasa

Rafi Sheikh

Malin Malmsjo

Magnus Cinthio

Affiliations

Soon will be listed here.

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.

Citing Articles

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