Micro‐computed tomography (microCT) of small animals has led to a more detailed and more accurate three‐dimensional (3D) view on different anatomical structures in the last years. Here, we present the cranial anatomy of two frog species providing descriptions of bone structures and soft tissues of the feeding apparatus with comments to possible relations to habitat and feeding ecology. Calyptocephalella gayi, known for its aquatic lifestyle, is not restricted to aquatic feeding but also feeds terrestrially using lingual prehension. This called for a detailed investigation of the morphology of its feeding apparatus and a comparison to a fully terrestrial species that is known to feed by lingual prehension such as Leptodactylus pentadactylus. These two frog species are of similar size, feed on similar diet but within different main habitats. MicroCT scans of both species were conducted in order to reconstruct the complete anatomical condition of the whole feeding apparatus for the first time. Differences in this regard are evident in the tongue musculature, which in L. pentadactylus is more massively built and with a broader interdigitating area of the two main muscles, the protractor musculus genioglossus and the retractor musculus hyoglossus. In contrast, the hyoid retractor (m. sternohyoideus) is more massive in the aquatic species C. gayi. Moreover, due to the different skull morphology, the origins of two of the five musculi adductores vary between the species. This study brings new insights into the relation of the anatomy of the feeding apparatus to the preferred feeding method via 3D imaging techniques. Contrary to the terrestrially feeding L. pentadactylus, the skeletal and muscular adaptations of the aquatic species C. gayi provide a clear picture of necessities prescribed by the habitat. Nevertheless, by keeping a certain amount of flexibility of the design of its feeding apparatus, C. gayi is able to employ various methods of feeding.
The growing use of multimodal high-resolution volumetric data in pre-clinical studies leads to challenges related to the management and handling of the large amount of these datasets. Contrarily to the clinical context, currently there are no standard guidelines to regulate the use of image compression in pre-clinical contexts as a potential alleviation of this problem. In this work, the authors study the application of lossy image coding to compress high-resolution volumetric biomedical data. The impact of compression on the metrics and interpretation of volumetric data was quantified for a correlated multimodal imaging study to characterize murine tumor vasculature, using volumetric high-resolution episcopic microscopy (HREM), micro-computed tomography (µCT), and micro-magnetic resonance imaging (µMRI). The effects of compression were assessed by measuring task-specific performances of several biomedical experts who interpreted and labeled multiple data volumes compressed at different degrees. We defined trade-offs between data volume reduction and preservation of visual information, which ensured the preservation of relevant vasculature morphology at maximum compression efficiency across scales. Using the Jaccard Index (JI) and the average Hausdorff Distance (HD) after vasculature segmentation, we could demonstrate that, in this study, compression that yields to a 256-fold reduction of the data size allowed to keep the error induced by compression below the inter-observer variability, with minimal impact on the assessment of the tumor vasculature across scales.
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