Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging
(2021) In Biomedical Optics Express 12(7). p.3836-3850- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4ab05725-4b94-4299-bede-693cca16e7c8
- author
- Khodaverdi, Azin LU ; Erlöv, Tobias LU ; Hult, Jenny LU ; Reistad, Nina LU ; Pekar-Lukacs, Agnes ; Albinsson, John LU ; Merdasa, Aboma LU ; Sheikh, Rafi LU ; Malmsjö, Malin LU and Cinthio, Magnus LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Hyperspectral imaging, Matched filtering, Nanosecond pulses, Optical absorption, Optical imaging, Photoacoustic imaging
- in
- Biomedical Optics Express
- volume
- 12
- issue
- 7
- pages
- 15 pages
- publisher
- Optical Society of America
- external identifiers
-
- scopus:85107856210
- pmid:34457383
- ISSN
- 2156-7085
- DOI
- 10.1364/BOE.422170
- language
- English
- LU publication?
- yes
- additional info
- 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.
- id
- 4ab05725-4b94-4299-bede-693cca16e7c8
- alternative location
- http://www.osapublishing.org/boe/abstract.cfm?URI=boe-12-7-3836
- date added to LUP
- 2021-06-07 23:55:02
- date last changed
- 2022-11-23 22:21:48
@article{4ab05725-4b94-4299-bede-693cca16e7c8, 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.}}, author = {{Khodaverdi, Azin and Erlöv, Tobias and Hult, Jenny and Reistad, Nina and Pekar-Lukacs, Agnes and Albinsson, John and Merdasa, Aboma and Sheikh, Rafi and Malmsjö, Malin and Cinthio, Magnus}}, issn = {{2156-7085}}, keywords = {{Hyperspectral imaging; Matched filtering; Nanosecond pulses; Optical absorption; Optical imaging; Photoacoustic imaging}}, language = {{eng}}, number = {{7}}, pages = {{3836--3850}}, publisher = {{Optical Society of America}}, series = {{Biomedical Optics Express}}, title = {{Automatic threshold selection algorithm to distinguish a tissue chromophore from the background in photoacoustic imaging}}, url = {{http://dx.doi.org/10.1364/BOE.422170}}, doi = {{10.1364/BOE.422170}}, volume = {{12}}, year = {{2021}}, }