نتایج جستجو برای: shape identification

تعداد نتایج: 593494  

Journal: :SIAM J. Imaging Sciences 2013
Yonathan Aflalo Ron Kimmel Dan Raviv

Local scale variations within the same species are common in nature. The shape matching puzzle poses fascinating questions, like how should we measure the discrepancy between a small dog with large ears and a large one with small ears? are there similar geometric structures that are common to an elephant and a giraffe? what is the morphometric similarity between a blue whale and a dolphin? Exis...

2017
S Praveen

Identification is necessary for humanitarian and emotional reasons and for many legal issues, particularly for family members. In recent reports, identification based on dental information is considered to be highly efficient, reliable, and rapid.4-7 Although many methods are followed for gender differentiation and age estimation, still identification of skeletal remains and decomposed bodies r...

Journal: :Medical image analysis 2003
Martin Styner Jeffrey A. Lieberman Guido Gerig

Statistical shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes and thus potentially discriminate between healthy and pathological structures. This paper describes a combined boundary and medial shape analysis based on two different shape descriptions applied to a study of the hippocampus shape abnormaliti...

1997
Nicolae Duta Milan Sonka

An improvement of the Active Shape procedure introduced by Cootes and Taylor is presented. The new automated brain segmenta-tion and interpretation approach incorporates a priori knowledge about neuroanatomic structures and their speciic structural relationships to provide robust segmentation and labeling. The method was trained in 8 MR brain images and tested in 19 brain images by comparison t...

2013
W. Thaller R. Zmugg U. Krispel M. Posch S. Havemann D. W. Fellner

The generative surface reconstruction problem can be stated like this: Given a finite collection of 3D shapes, create a small set of functions that can be combined to generate the given shapes procedurally. We propose generative fact labeling (GFL) as an attempt to organize the iterative process of shape analysis and shape synthesis in a systematic way. We present our results for the reconstruc...

Journal: :The Proceedings of the Annual Convention of the Japanese Psychological Association 2017

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