Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle
Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of “smartphones” is not restricted by limited exper...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-06-01
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| Series: | Diagnostics |
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| Online Access: | http://www.mdpi.com/2075-4418/6/2/24 |
| _version_ | 1798043159513530368 |
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| author | Ewert Linder Sami Varjo Cecilia Thors |
| author_facet | Ewert Linder Sami Varjo Cecilia Thors |
| author_sort | Ewert Linder |
| collection | DOAJ |
| description | Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of “smartphones” is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and “micro swimmers” of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the “vinegar eel.” The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as “diagnostic fingerprints.” |
| first_indexed | 2024-04-11T22:45:42Z |
| format | Article |
| id | doaj.art-c788d33bf1434289bad1b182aec1a664 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-04-11T22:45:42Z |
| publishDate | 2016-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-c788d33bf1434289bad1b182aec1a6642022-12-22T03:58:47ZengMDPI AGDiagnostics2075-44182016-06-01622410.3390/diagnostics6020024diagnostics6020024Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life CycleEwert Linder0Sami Varjo1Cecilia Thors2Department of Microbiology, Tumor and Cell Biuology, Karolinska Institutet, SE-17177 Stockholm, SwedenCenter for Machine Vision and Signal Analysis, University of Oulu, FI-90014 Oulu, FinlandPublic Health Agency of Sweden, SE-17182 Solna, SwedenImaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of “smartphones” is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and “micro swimmers” of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the “vinegar eel.” The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as “diagnostic fingerprints.”http://www.mdpi.com/2075-4418/6/2/24POC diagnosticsschistosomiasismotility patternsmini-microscopesimage analysiscomputer visiontelemedicineneglected diseasesremote sensingspectrogram |
| spellingShingle | Ewert Linder Sami Varjo Cecilia Thors Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle Diagnostics POC diagnostics schistosomiasis motility patterns mini-microscopes image analysis computer vision telemedicine neglected diseases remote sensing spectrogram |
| title | Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle |
| title_full | Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle |
| title_fullStr | Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle |
| title_full_unstemmed | Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle |
| title_short | Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle |
| title_sort | mobile diagnostics based on motion a close look at motility patterns in the schistosome life cycle |
| topic | POC diagnostics schistosomiasis motility patterns mini-microscopes image analysis computer vision telemedicine neglected diseases remote sensing spectrogram |
| url | http://www.mdpi.com/2075-4418/6/2/24 |
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