Ubiquitous in eukaryotic URLanisms, the flagellum is a well-studied and URLanelle that is well-known to be responsible for motility in a variety URLanisms. Pertinent to multiple areas of active scientific interest is the understanding of their substructures, mechanical regulation, and beating patterns, with the latter being of particular relevance to the investigation of motile flagellated URLanisms. Commonly necessitated in their study is the capability to image and subsequently track the movement of one or more flagella using videomicroscopy, requiring digital isolation and location of the flagellum within a sequence of frames. Such a process in general currently requires some researcher input, providing some manual estimate or reliance on an experiment-specific heuristic to correctly identify and track the motion of a flagellum. Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella appear to be of approximately constant width when viewed with typical optics. This approximate morphological characteristic, inherent in the ultrastructure of URLanelle, is conserved across many eukaryotes. We demonstrate the effectiveness of the algorithm by application to captured videomicroscopy of Leishmania mexicana, a parasitic monoflagellate of the family Trypanosomatidae and the cause of a major but neglected human disease, leishmaniasis. Both high accuracy and remarkable throughput are achieved via this unsupervised method, obtaining results comparable in quality to previous studies of closely-related species but achieved without the need for precursory measurements or the development of a specialised heuristic . Further, we process a dataset documenting a canonical microswimmer that has accessory flagellar structures, the motile human spermatozoon, thus.. .
Ubiquitous in URLanisms, the flagellum is a URLanelle that is well-known to be responsible for motility in a variety URLanisms. Commonly necessitated in their study is the capability to image and subsequently track the movement of one or more flagella using videomicroscopy, requiring digital isolation and location of the flagellum within a sequence of frames. Such a process in general currently requires some researcher input, providing some manual estimate or reliance on an experiment-specific heuristic to correctly identify and track the motion of a flagellum. Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella are of approximately constant width when viewed by microscopy. We demonstrate the effectiveness of the algorithm by application to captured videomicroscopy of Leishmania mexicana, a parasitic monoflagellate of the family Trypanosomatidae . ImageJ Macros for flagellar identification are provided, and high accuracy and remarkable throughput are achieved via this unsupervised method, obtaining results comparable in quality to previous studies of closely-related species but achieved without the need for precursory measurements or the development of a specialised heuristic , enabling in general the automated generation of digitised kinematic descriptions of flagellar beating from videomicroscopy .
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eukaryotic
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well-studied and
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Pertinent to multiple areas of active scientific interest is the understanding of their substructures, mechanical regulation, and beating patterns, with the latter being of particular relevance to the investigation of motile flagellated URLanisms.
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appear to be
are
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with typical optics. This approximate morphological characteristic, inherent in the ultrastructure of URLanelle, is conserved across many eukaryotes.
by microscopy.
R
and the cause of a major but neglected human disease, leishmaniasis. Both
. ImageJ Macros for flagellar identification are provided, and
R
. Further, we process a dataset documenting a canonical microswimmer that has accessory flagellar structures, the motile human spermatozoon, thus..
, enabling in general the automated generation of digitised kinematic descriptions of flagellar beating from videomicroscopy