ArticleAnalytical chemistry2015
Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.
Article in Analytical chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 25 citations in OpenAlex.
- Multiplexed glycan immunofluorescence identification of pancreatic cancer cell subpopulations in both tumor and blood samples.Science advances · 2025Article
- Glycosaminoglycan microarrays for studying glycosaminoglycan-protein systems.Carbohydrate polymers · 2024Review
- Mechanisms and Minimization of False Discovery of Metabolic Bioorthogonal Noncanonical Amino Acid Proteomics.Rejuvenation research · 2022Article
- Autoimmunity in Human CE: Correlative with The Fertility Status of The CE Cyst.Helminthologia · 2022Article
- Role of non-coding RNAs in tumor progression and metastasis in pancreatic cancer.Cancer metastasis reviews · 2021Review
- Imaging Mass Spectrometry and Lectin Analysis of N-Linked Glycans in Carbohydrate Antigen-Defined Pancreatic Cancer Tissues.Molecular & cellular proteomics : MCP · 2021Article
- Tools for generating and analyzing glycan microarray data.Beilstein journal of organic chemistry · 2020Review
- Automated Identification and Quantification of Signals in Multichannel Immunofluorescence Images: The SignalFinder-IF Platform.The American journal of pathology · 2019Article
- FluoroCellTrack: An algorithm for automated analysis of high-throughput droplet microfluidic data.PloS one · 2019Article
- Quantitative analysis of conjunctival microvasculature imaged using optical coherence tomography angiography.Eye and vision (London, England) · 2019Article
- Deciphering Protein Glycosylation by Computational Integration of On-chip Profiling, Glycan-array Data, and Mass Spectrometry.Molecular & cellular proteomics : MCP · 2019Article
- Current applications of antibody microarrays.Clinical proteomics · 2018Review
- The CA19-9 and Sialyl-TRA Antigens Define Separate Subpopulations of Pancreatic Cancer Cells.Scientific reports · 2017Article
- Characterizing Protein Glycosylation through On-Chip Glycan Modification and Probing.Analytical chemistry · 2016Article
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Authors and funding
12 authors at 4 institutions in 1 country.
Funding
Abstract
Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.