Results 121 to 130 of about 32,154 (292)

Early synapsids neurosensory diversity revealed by CT and synchrotron scanning

open access: yesThe Anatomical Record, EarlyView.
Abstract Non‐mammaliaform synapsids (NMS) represent the closest relatives of today's mammals among the early amniotes. Exploring their brain and nervous system is key to understanding how mammals evolved. Here, using CT and Synchrotron scanning, we document for the first time three extreme cases of neurosensory and behavioral adaptations that probe ...
J. Benoit   +6 more
wiley   +1 more source

A Simple Specific Functional Test for SCD: VEMPs to High Frequency (4,000Hz) Stimuli—Their Origin and Explanation

open access: yesFrontiers in Neurology, 2020
Ian S. Curthoys   +3 more
doaj   +1 more source

Predicting ecology and hearing sensitivities in Parapontoporia—An extinct long‐snouted dolphin

open access: yesThe Anatomical Record, EarlyView.
Abstract Analyses of the cetacean (whale and dolphin) inner ear provide glimpses into the ecology and evolution of extinct and extant groups. The paleoecology of the long‐snouted odontocete (toothed whale) group, Parapontoporia, is primarily marine with its depositional context also suggesting freshwater tolerance.
Joyce Sanks, Rachel Racicot
wiley   +1 more source

Bioimaging of sense organs and the central nervous system in extant fishes and reptiles in situ: A review

open access: yesThe Anatomical Record, EarlyView.
Bioimaging of the sense organs and brain of fishes and reptiles. Left panel: 3D reconstruction of the head and brain of the deep‐sea viperfish Chauliodus sloani following diceCT. Right panel: A 3D reconstruction of a 70‐day‐old embryo head of the bearded dragon Pogona vitticeps following diceCT, showing the position of the segmented brain within the ...
Shaun P. Collin   +9 more
wiley   +1 more source

Segmentation of cortical bone, trabecular bone, and medullary pores from micro‐CT images using 2D and 3D deep learning models

open access: yesThe Anatomical Record, EarlyView.
Abstract Computed tomography (CT) enables rapid imaging of large‐scale studies of bone, but those datasets typically require manual segmentation, which is time‐consuming and prone to error. Convolutional neural networks (CNNs) offer an automated solution, achieving superior performance on image data.
Andrew H. Lee   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy