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Graph-based image decoding for multiplexed in situ RNA detection
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- Partel, Gabriele, 1988- (author)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Science for Life Laboratory, SciLifeLab
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- Wählby, Carolina, professor, 1974- (author)
- Uppsala universitet,Bildanalys och människa-datorinteraktion,Science for Life Laboratory, SciLifeLab,Avdelningen för visuell information och interaktion
- (creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2021
- 2021
- English.
- In: 2020 25th International Conference on Pattern Recognition (ICPR). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728188089 ; , s. 3783-3790
- Conference paper (peer-reviewed)
Abstract
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- Image-based multiplexed in situ RNA detectionmakes it possible to map the spatial gene expression of hundreds to thousands of genes in parallel, and thus discern at the sametime a large numbers of different cell types to better understand tissue development, heterogeneity, and disease. Fluorescent signals are detected over multiple fluorescent channels and imaging rounds and decoded in order to identify RNA molecules in their morphological context. Here we present a graph-based decoding approach that models the decoding process as a network flow problem jointly optimizing observation likelihoods and distances of signal detections, thus achieving robustness with respect to noise and spatial jitter of the fluorescent signals. We evaluated our method on synthetic data generated at different experimental conditions, and on real data of in situ RNA sequencing, comparng results with respect to alternative and gold standard imagede coding pipelines.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
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