Titlebook: Marginal Space Learning for Medical Image Analysis; Efficient Detection Yefeng Zheng,Dorin Comaniciu Book 2014 Springer Science+Business M

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ally infected cells and normal allogeneic cells without prior sensitization (1). NK killing is distinct from major histocompatibility complex (MHC)-restricted cytotoxic T lymphocyte (CTL) killing because both syngeneic and allogeneic targets can be lysed. NK cells are defined as lymphocytes that hav

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Comparison of Marginal Space Learning and Full Space Learning in 2D,pare the performance of the MSL and Full Space Learning. A thorough comparison experiment on the LV detection in MRI images shows that the MSL significantly outperforms the FSL, in both speed and accuracy.

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Constrained Marginal Space Learning,framework. The prior distribution of the object position is learned based on the statistics of the distance from the object center to volume border, and the test hypotheses of the orientation and scale are generated using an example-based sampling strategy from the training set. Furthermore, we empl

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Optimal Mean Shape for Nonrigid Object Detection and Segmentation, population. The anisotropic similarity transformation from the optimal mean shape to each individual training shape provides the ground truth of the pose parameters learned through the Marginal Space Learning (MSL). After the alignment with the estimated object pose, the optimal mean shape provides

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Nonrigid Object Segmentation: Application to Four-Chamber Heart Segmentation,onents described in previous chapters into a complete segmentation system. In addition, simple and efficient methods based on mesh resampling are developed to establish mesh point correspondence, required to train a mean shape for shape initialization and build a statistical shape model for object b

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