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Hyperspectral characterization of re-epithelialization in an in vitro wound model.体外伤口模型中再上皮化的高光谱特征描述。
J Biophotonics. 2020 Oct;13(10):e202000108. doi: 10.1002/jbio.202000108. Epub 2020 Jul 13.
2
Deep learning applied to hyperspectral endoscopy for online spectral classification.深度学习在高光谱内窥镜中的应用:在线光谱分类。
Sci Rep. 2020 Mar 3;10(1):3947. doi: 10.1038/s41598-020-60574-6.
3
Cytotoxicity and effect on wound re-epithelialization after topical administration of tranexamic acid.局部给予氨甲环酸后的细胞毒性和对伤口再上皮化的影响。
BJS Open. 2019 Sep 26;3(6):840-851. doi: 10.1002/bjs5.50192. eCollection 2019 Dec.
4
Evaluation of hyperspectral NIRS for quantitative measurements of tissue oxygen saturation by comparison to time-resolved NIRS.通过与时间分辨近红外光谱技术对比,评估高光谱近红外光谱技术用于定量测量组织氧饱和度的效果。
Biomed Opt Express. 2019 Aug 23;10(9):4789-4802. doi: 10.1364/BOE.10.004789. eCollection 2019 Sep 1.
5
Hyperspectral imaging of human skin aided by artificial neural networks.借助人工神经网络的人体皮肤高光谱成像
Biomed Opt Express. 2019 Jun 24;10(7):3545-3559. doi: 10.1364/BOE.10.003545. eCollection 2019 Jul 1.
6
Intraoperative multispectral and hyperspectral label-free imaging: A systematic review of in vivo clinical studies.术中多光谱和高光谱无标记成像:体内临床研究的系统综述
J Biophotonics. 2019 Sep;12(9):e201800455. doi: 10.1002/jbio.201800455. Epub 2019 Apr 29.
7
Physiological and structural characterization of human skin in vivo using combined photothermal radiometry and diffuse reflectance spectroscopy.结合光热辐射测量法和漫反射光谱法对人体皮肤进行体内生理和结构特征分析。
Biomed Opt Express. 2019 Jan 29;10(2):944-960. doi: 10.1364/BOE.10.000944. eCollection 2019 Feb 1.
8
Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery.高光谱成象用于组织分类,实现智能腹腔镜结直肠手术。
J Biomed Opt. 2019 Jan;24(1):1-9. doi: 10.1117/1.JBO.24.1.016002.
9
Hyperspectral imaging in perfusion and wound diagnostics - methods and algorithms for the determination of tissue parameters.灌注与伤口诊断中的高光谱成像——组织参数测定的方法与算法
Biomed Tech (Berl). 2018 Oct 25;63(5):547-556. doi: 10.1515/bmt-2017-0155.
10
Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma .用于导管癌组织学评估的高光谱成像与K均值分类
Front Oncol. 2018 Feb 7;8:17. doi: 10.3389/fonc.2018.00017. eCollection 2018.

利用尺度不变性:一种针对伤口高光谱图像的顶层目标逆模型。

Exploiting scale-invariance: a top layer targeted inverse model for hyperspectral images of wounds.

作者信息

Bjorgan Asgeir, Randeberg Lise Lyngsnes

机构信息

Department of Electronic Systems, NTNU Norwegian University of Science and Technology, Trondheim, Norway.

出版信息

Biomed Opt Express. 2020 Aug 17;11(9):5070-5091. doi: 10.1364/BOE.399636. eCollection 2020 Sep 1.

DOI:10.1364/BOE.399636
PMID:33014601
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7510863/
Abstract

Detection of re-epithelialization in wound healing is important, but challenging. Hyperspectral imaging can be used for non-destructive characterization, but efficient techniques are needed to extract and interpret the information. An inverse photon transport model suitable for characterization of re-epithelialization is validated and explored in this study. It exploits scale-invariance to enable fitting of the epidermal skin layer only. Monte Carlo simulations indicate that the fitted layer transmittance and reflectance spectra are unique, and that there exists an infinite number of coupled parameter solutions. The method is used to explain the optical behavior of and detect re-epithelialization in an in vitro wound model.

摘要

检测伤口愈合过程中的再上皮化很重要,但具有挑战性。高光谱成像可用于无损表征,但需要有效的技术来提取和解释信息。本研究验证并探索了一种适用于表征再上皮化的逆光子传输模型。它利用尺度不变性仅对表皮层进行拟合。蒙特卡罗模拟表明,拟合的层透射率和反射率光谱是唯一的,并且存在无限数量的耦合参数解。该方法用于解释体外伤口模型中的光学行为并检测再上皮化。