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

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

Skåne University Hospital

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	3836-3850
Number of pages	15
Journal	Biomedical Optics Express
Volume	12
Issue number	7
DOIs	https://doi.org/10.1364/BOE.422170
Publication status	Published - 2021

Subject classification (UKÄ)

Ophthalmology
Radiology and Medical Imaging

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10.1364/BOE.422170

http://www.osapublishing.org/boe/abstract.cfm?URI=boe-12-7-3836

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@article{4ab057254b944299bede693cca16e7c8,

title = "Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging",

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.",

keywords = "Hyperspectral imaging, Matched filtering, Nanosecond pulses, Optical absorption, Optical imaging, Photoacoustic imaging",

author = "Azin Khodaverdi and Tobias Erl{\"o}v and Jenny Hult and Nina Reistad and Agnes Pekar-Lukacs and John Albinsson and Aboma Merdasa and Rafi Sheikh and Malin Malmsj{\"o} and Magnus Cinthio",

note = "Funding Information: Funding. Vetenskapsr{\aa}det; Lunds Tekniska H{\"o}gskola, Lunds universitet; IngaBritt och Arne Lundbergs Forskn-ingsstiftelse; Stiftelsen f{\"o}r Synskadade i f.d. Malm{\"o}hus l{\"a}n; Stiftelsen Kronprinsessan Margaretas Arbetsn{\"a}mnd f{\"o}r Synskadade; Lund University Grant for Research Infrastructure; Sk{\aa}ne County Council{\textquoteright}s Research and Development Foundation; Sk{\aa}nes universitetssjukhus; Swedish Government Grant for Clinical Research (ALF); Knut och Alice Wallenbergs Stiftelse. Publisher Copyright: {\textcopyright} 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

doi = "10.1364/BOE.422170",

language = "English",

volume = "12",

pages = "3836--3850",

journal = "Biomedical Optics Express",

issn = "2156-7085",

publisher = "Optical Society of America",

number = "7",

}

TY - JOUR

T1 - Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging

AU - Khodaverdi, Azin

AU - Erlöv, Tobias

AU - Hult, Jenny

AU - Reistad, Nina

AU - Pekar-Lukacs, Agnes

AU - Albinsson, John

AU - Merdasa, Aboma

AU - Sheikh, Rafi

AU - Malmsjö, Malin

AU - Cinthio, Magnus

N1 - Funding Information: Funding. Vetenskapsrådet; Lunds Tekniska Högskola, Lunds universitet; IngaBritt och Arne Lundbergs Forskn-ingsstiftelse; Stiftelsen för Synskadade i f.d. Malmöhus län; Stiftelsen Kronprinsessan Margaretas Arbetsnämnd för Synskadade; Lund University Grant for Research Infrastructure; Skåne County Council’s Research and Development Foundation; Skånes universitetssjukhus; Swedish Government Grant for Clinical Research (ALF); Knut och Alice Wallenbergs Stiftelse. Publisher Copyright: © 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Hyperspectral imaging

KW - Matched filtering

KW - Nanosecond pulses

KW - Optical absorption

KW - Optical imaging

KW - Photoacoustic imaging

UR - https://www.scopus.com/pages/publications/85107856210

U2 - 10.1364/BOE.422170

DO - 10.1364/BOE.422170

M3 - Article

C2 - 34457383

SN - 2156-7085

VL - 12

SP - 3836

EP - 3850

JO - Biomedical Optics Express

JF - Biomedical Optics Express

IS - 7

ER -

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

Abstract

Subject classification (UKÄ)

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