Sparse shape representation using the laplace-beltrami eigenfunctions and its appli- cation to modeling subcortical structures, in: Mathematical Methods in Biomedi- cal Image Analysis (MMBIA), 2012 IEEE Workshop on, IEEE. pp. 25-32.Kim SG, Chung MK, Schaefer SM, et al. Sparse shape ...
Given a classified probabilistic shape dictionary, and an image with a shape similar to some of the elements in the dictionary, this letter introduces a sparse representation based framework with a twofold goal. First, to select a sparse shape combination from the dictionary that best represents th...
Instead of the strong request of the pre-segmentation of cine MRI in the same session, we use the sparse representation method to model the myocardium shape. Data from the Cardiac MR Left Ventricle Segmentation Challenge (2009) are used to build the shape template repository. The method of ...
Our method works by combining random forest (RF) regression based landmark de- tection with sparse shape composition model based landmark correction. Validation on 100 cephalometric X-ray images show that 77.79% land- marks can be detected by our method with an error less than 4.0 mm. 展开 ...
Some medical data sets, such as the skull, are inherently sparse, with voxel occupancy rates as low as 10%. Since only non-empty voxels carry geometric information of the 3D shape, a sparse convolutional neural network (CNN)2,3,4,5 can save both memory and computational effort. In our ...
Issue and/or context: As tracked on issue #2407 / [sc-51048]. Note that the intended Python and R API changes are all agreed on and finalized as described in #2407. Changes: This is a split-out to ...
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sparseautoencodernetworksstatisticalshapemodellingtrochleardysplasiatrochlearmorphologyBackground The quantitative morphological analysis of the trochlear region in the distal femur and the precise staging of the potential dysplastic condition constitute a key point for the use of personalized treatment options for...
This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver...
Sparse representation-based classifier and its var Ding,Hongbing - 《IEEE Geoscience & Remote Sensing Letters》 被引量: 0发表: 2015年 ieee journal of selected topics in applied earth observations and remote sensing 1 hyperspectral image classification via shape-adaptive joint sparse repre... Sparse...