3,490 research outputs found
True-color 3D rendering of human anatomy using surface-guided color sampling from cadaver cryosection image data: A practical approach Jon Jatsu Azkue
Three-dimensional computer graphics are increasingly used for scientific visualization and for communicating anatomical knowledge and data. This study presents a practical method to produce true-color 3D surface renditions of anatomical structures. The procedure involves extracting the surface geometry of the structure of interest from a stack of cadaver cryosection images, using the extracted surface as a probe to retrieve color information from cryosection data, and mapping sampled colors back onto the surface model to produce a true-color rendition. Organs and body parts can be rendered separately or in combination to create custom anatomical scenes. By editing the surface probe, structures of interest can be rendered as if they had been previously dissected or prepared for anatomical demonstration. The procedure is highly flexible and nondestructive, offering new opportunities to present and communicate anatomical information and knowledge in a visually realistic manner. The technical procedure is described, including freely available open-source software tools involved in the production process, and examples of color surface renderings of anatomical structures are provided
Study and Comparison of Surface Roughness Measurements
National audienceThis survey paper focus on recent researches whose goal is to optimize treatments on 3D meshes, thanks to a study of their surface features, and more precisely their roughness and saliency. Applications like watermarking or lossy compression can benefit from a precise roughness detection, to better hide the watermarks or quantize coarsely these areas, without altering visually the shape. Despite investigations on scale dependence leading to multi-scale approaches, an accurate roughness or pattern characterization is still lacking, but challenging for those treatments. We think there is still room for investigations that could benefit from the power of the wavelet analysis or the fractal models. Furthermore only few works are now able to differentiate roughness from saliency, though it is essential for faithfully simplifying or denoising a 3D mesh. Hence we have investigated roughness quantification methods for analog surfaces, in several domains of physics. Some roughness parameters used in these fields and the additionnal information they bring are finally studied, since we think an adaptation for 3D meshes could be beneficial
Orbital and Maxillofacial Computer Aided Surgery: Patient-Specific Finite Element Models To Predict Surgical Outcomes
This paper addresses an important issue raised for the clinical relevance of
Computer-Assisted Surgical applications, namely the methodology used to
automatically build patient-specific Finite Element (FE) models of anatomical
structures. From this perspective, a method is proposed, based on a technique
called the Mesh-Matching method, followed by a process that corrects mesh
irregularities. The Mesh-Matching algorithm generates patient-specific volume
meshes from an existing generic model. The mesh regularization process is based
on the Jacobian matrix transform related to the FE reference element and the
current element. This method for generating patient-specific FE models is first
applied to Computer-Assisted maxillofacial surgery, and more precisely to the
FE elastic modelling of patient facial soft tissues. For each patient, the
planned bone osteotomies (mandible, maxilla, chin) are used as boundary
conditions to deform the FE face model, in order to predict the aesthetic
outcome of the surgery. Seven FE patient-specific models were successfully
generated by our method. For one patient, the prediction of the FE model is
qualitatively compared with the patient's post-operative appearance, measured
from a Computer Tomography scan. Then, our methodology is applied to
Computer-Assisted orbital surgery. It is, therefore, evaluated for the
generation of eleven patient-specific FE poroelastic models of the orbital soft
tissues. These models are used to predict the consequences of the surgical
decompression of the orbit. More precisely, an average law is extrapolated from
the simulations carried out for each patient model. This law links the size of
the osteotomy (i.e. the surgical gesture) and the backward displacement of the
eyeball (the consequence of the surgical gesture)
Multilinear Wavelets: A Statistical Shape Space for Human Faces
We present a statistical model for D human faces in varying expression,
which decomposes the surface of the face using a wavelet transform, and learns
many localized, decorrelated multilinear models on the resulting coefficients.
Using this model we are able to reconstruct faces from noisy and occluded D
face scans, and facial motion sequences. Accurate reconstruction of face shape
is important for applications such as tele-presence and gaming. The localized
and multi-scale nature of our model allows for recovery of fine-scale detail
while retaining robustness to severe noise and occlusion, and is
computationally efficient and scalable. We validate these properties
experimentally on challenging data in the form of static scans and motion
sequences. We show that in comparison to a global multilinear model, our model
better preserves fine detail and is computationally faster, while in comparison
to a localized PCA model, our model better handles variation in expression, is
faster, and allows us to fix identity parameters for a given subject.Comment: 10 pages, 7 figures; accepted to ECCV 201
Finite Element Based Tracking of Deforming Surfaces
We present an approach to robustly track the geometry of an object that
deforms over time from a set of input point clouds captured from a single
viewpoint. The deformations we consider are caused by applying forces to known
locations on the object's surface. Our method combines the use of prior
information on the geometry of the object modeled by a smooth template and the
use of a linear finite element method to predict the deformation. This allows
the accurate reconstruction of both the observed and the unobserved sides of
the object. We present tracking results for noisy low-quality point clouds
acquired by either a stereo camera or a depth camera, and simulations with
point clouds corrupted by different error terms. We show that our method is
also applicable to large non-linear deformations.Comment: additional experiment
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