Results 81 to 90 of about 1,476 (141)

Rootlets-based registration to the PAM50 spinal cord template. [PDF]

open access: yesImaging Neurosci (Camb)
Bédard S   +4 more
europepmc   +1 more source

Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: A multi-reader study. [PDF]

open access: yesNeuroimage Clin
Di Noto T   +11 more
europepmc   +1 more source

Exploring fern pathosystems and immune receptors to bridge gaps in plant immunity. [PDF]

open access: yesBMC Biol
Castel B   +6 more
europepmc   +1 more source

Bacterial chromatin remodeling associated with transcription-induced domains at pathogenicity Islands. [PDF]

open access: yesNat Commun
Kortebi M   +7 more
europepmc   +1 more source

Extracellular vesicles from glycolytic mesenchymal stromal cells restrain arthritis progression via IL-10-Producing T and B cells. [PDF]

open access: yesTheranostics
Lara-Barba E   +38 more
europepmc   +1 more source
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3D manipulation of motion imagery

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101), 2002
We present a set of automatic methods for the recovery and refinement of 3D scene geometry and camera poses from motion imagery. First, we present a two-frame "direct" method, which simultaneously estimates both relative pose between the cameras and 3D scene geometry using information from the images alone.
Rakesh Kumar 0001   +4 more
openaire   +1 more source

3D-segmentation and display of tomographic imagery

[1988 Proceedings] 9th International Conference on Pattern Recognition, 2003
Using the Marr-Hildreth operator with a subsequent closing algorithm, it is possible to determine the main constituents of the human head from magnetic resonance image data. With use of the segmentation results in a generalized voxel model one can generate images that are very similar to what is known from real anatomy.
Karl Heinz Hoehne   +4 more
openaire   +1 more source

Knowledge-Guided Segmentation of 3D Imagery

Graphical Models and Image Processing, 1996
This paper presents a computationally efficient and robust approach to locate, label, and isolate three-dimensional (3D) structures from discrete 3D imagery. The emphasis is placed on extracting a convex, singly connected 3D structure of interest imbedded in discrete, volumetric data sets that are sparse, noisy, and possibly misleading.
Norberto Ezquerra, Rakesh Mullick
openaire   +1 more source

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