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Evaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis

Analyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mas... Full description

Journal Title: Journal of the American Society for Mass Spectrometry 2018-10-15, Vol.29 (12), p.2467-2470
Main Author: Ekelöf, Måns
Other Authors: Garrard, Kenneth P , Judd, Rika , Rosen, Elias P , Xie, De-Yu , Kashuba, Angela D. M , Muddiman, David C
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: New York: Springer US
ID: ISSN: 1044-0305
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title: Evaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis
format: Article
creator:
  • Ekelöf, Måns
  • Garrard, Kenneth P
  • Judd, Rika
  • Rosen, Elias P
  • Xie, De-Yu
  • Kashuba, Angela D. M
  • Muddiman, David C
subjects:
  • ALGORITHMS
  • Analytical Chemistry
  • ANIMAL TISSUES
  • Animals
  • Application Note
  • Article
  • beverages
  • Bioinformatics
  • Biotechnology
  • Chemistry
  • Chemistry and Materials Science
  • COMPUTERIZED SIMULATION
  • DATA ANALYSIS
  • Data sets
  • Digital imaging
  • DISTRIBUTION
  • DRUGS
  • food
  • Homeopathy
  • IMAGE PROCESSING
  • Image Processing, Computer-Assisted - methods
  • Image Recognition
  • Lymph Nodes - chemistry
  • Lymph Nodes - metabolism
  • Macaca mulatta
  • Maraviroc - pharmacokinetics
  • Mass spectrometry
  • Mass Spectrometry - methods
  • Mass Spectrometry Imaging
  • MASS SPECTROSCOPY
  • Materia medica and therapeutics
  • MATHEMATICAL METHODS AND COMPUTING
  • Metabolites
  • Methods
  • Models, Theoretical
  • Molecular Imaging - methods
  • Object recognition
  • Organic Chemistry
  • Plant Leaves - chemistry
  • Proteomics
  • Rankings
  • Scientific imaging
  • Similarity
  • Spectroscopy
  • SSIM
  • Therapeutics
  • Tissue Distribution
ispartof: Journal of the American Society for Mass Spectrometry, 2018-10-15, Vol.29 (12), p.2467-2470
description: Analyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. Graphical Abstract ᅟ
language: eng
source:
identifier: ISSN: 1044-0305
fulltext: no_fulltext
issn:
  • 1044-0305
  • 1879-1123
url: Link


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titleEvaluation of Digital Image Recognition Methods for Mass Spectrometry Imaging Data Analysis
creatorEkelöf, Måns ; Garrard, Kenneth P ; Judd, Rika ; Rosen, Elias P ; Xie, De-Yu ; Kashuba, Angela D. M ; Muddiman, David C
creatorcontribEkelöf, Måns ; Garrard, Kenneth P ; Judd, Rika ; Rosen, Elias P ; Xie, De-Yu ; Kashuba, Angela D. M ; Muddiman, David C
descriptionAnalyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. Graphical Abstract ᅟ
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subjectALGORITHMS ; Analytical Chemistry ; ANIMAL TISSUES ; Animals ; Application Note ; Article ; beverages ; Bioinformatics ; Biotechnology ; Chemistry ; Chemistry and Materials Science ; COMPUTERIZED SIMULATION ; DATA ANALYSIS ; Data sets ; Digital imaging ; DISTRIBUTION ; DRUGS ; food ; Homeopathy ; IMAGE PROCESSING ; Image Processing, Computer-Assisted - methods ; Image Recognition ; Lymph Nodes - chemistry ; Lymph Nodes - metabolism ; Macaca mulatta ; Maraviroc - pharmacokinetics ; Mass spectrometry ; Mass Spectrometry - methods ; Mass Spectrometry Imaging ; MASS SPECTROSCOPY ; Materia medica and therapeutics ; MATHEMATICAL METHODS AND COMPUTING ; Metabolites ; Methods ; Models, Theoretical ; Molecular Imaging - methods ; Object recognition ; Organic Chemistry ; Plant Leaves - chemistry ; Proteomics ; Rankings ; Scientific imaging ; Similarity ; Spectroscopy ; SSIM ; Therapeutics ; Tissue Distribution
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15DISTRIBUTION
16DRUGS
17food
18Homeopathy
19IMAGE PROCESSING
20Image Processing, Computer-Assisted - methods
21Image Recognition
22Lymph Nodes - chemistry
23Lymph Nodes - metabolism
24Macaca mulatta
25Maraviroc - pharmacokinetics
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22Lymph Nodes - chemistry
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24Macaca mulatta
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44SSIM
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abstractAnalyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. Graphical Abstract ᅟ
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pmid30324263
doi10.1007/s13361-018-2073-0
orcididhttps://orcid.org/0000-0003-2216-499X
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