Extracting Consistent and Manifold Interfaces from Multi-valued Volume Data Sets

Bischoff, Stephan; Kobbelt, Leif

doi:10.1007/3-540-32137-3_57

Cited by 10 publications

(13 citation statements)

References 4 publications

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“…Distance maps of registered structures can be merged to yield an average. Reconstructing multiple structures can be achieved by integrating the distance maps of all structures into a single one and applying specialized surface extraction algorithms (Bischoff and Kobbelt, 2006). However, for highly elongated structures, like tracts, outlines in adjacent sections do not necessarily overlap and therefore shape-based interpolation does not yield a meaningful implicit representation in which the outlines are connected.…”

Section: Bootstrap Approach For the Construction Of A Mean Atlasmentioning

confidence: 99%

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A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data

et al. 2010

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Section: Bootstrap Approach For the Construction Of A Mean Atlasmentioning

confidence: 99%

“…To reconstruct the surface of the reference volume, an approach which expands singular vertices and edges, was used (Bischoff and Kobbelt, 2006). This algorithm also allows to incorporate a priori information by considering that two structures are delimited by another one.…”

Section: Surface Reconstructionmentioning

confidence: 99%

A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data

et al. 2010

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“…This solution can be obtained by using the subdivision ideas presented in [1]. We will also investigate the extraction of other attribute maps like material maps, normal maps and relief textures.…”

Section: Discussionmentioning

confidence: 98%

Fast Polygonization and Texture Map Extraction from Volumetric Objects Based on Surface Fairing Using a Modified Discrete Laplacian Operator

Muniz

Montenegro

Clua

2010

2010 Brazilian Symposium on Games and Digital Entertainment

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“…Based on a caref ul annotation of a ref erence volume with each voxel belonging to eith er exactly one of the anatomical structures o r to th e b ackground a tr iangular mesh i s g enerated f or all str uctures u sing a multi-region tr iangulation algorithm [3]. The result, which is a joint mesh for all structures with common surfaces for adjacent parts, preserves the complex adjacency relatio nships of th e brain.…”

Section: The Brain Modelmentioning

confidence: 99%

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

Kneser

Lehmann

Geller

et al. 2009

Medical Imaging 2009: Computer-Aided Diagnosis

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To m ake accu rate deci sions based on i maging data, radiolog ists must as sociate t he viewed i maging data with t he corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or am biguous findings are pres ent, external knowledge sources such as medical encyclopedias are con sulted. T hese s ources are acces sed u sing keywords t ypically de scribing a natomical s tructures, image findings, pathologies.In th is paper we pres ent o ur v ision of how a patie nt's i maging data can be a utomatically e nhanced with an atomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to acces s an atomical des criptions, inf ormation abou t path ologies an d i mage findings. O n th e ot her h and we envision e ncyclopedias to contain links to region-and finding-specific i mage processing algorithms. T hen a f inding is evaluated on an image by applying the respective algorithm in the associated anatomical region.Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain i mages. Thereby we develop a co mplex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We dem onstrate the validity b y a nalyzing t he results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.

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Extracting Consistent and Manifold Interfaces from Multi-valued Volume Data Sets

Cited by 10 publications

References 4 publications

A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data

A mean three-dimensional atlas of the human thalamus: Generation from multiple histological data

Fast Polygonization and Texture Map Extraction from Volumetric Objects Based on Surface Fairing Using a Modified Discrete Laplacian Operator

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

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