Feature-based groupwise registration by hierarchical anatomical correspondence detection
نویسندگان
چکیده
منابع مشابه
Feature-based groupwise registration by hierarchical anatomical correspondence detection.
Groupwise registration has been widely investigated in recent years due to its importance in analyzing population data in many clinical applications. To our best knowledge, most of the groupwise registration algorithms only utilize the intensity information. However, it is well known that using intensity only is not sufficient to achieve the anatomically sound correspondences in medical image r...
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We present a novel feature-based groupwise registration method to simultaneously warp the subjects towards the common space. Due to the complexity of the groupwise registration, we resort to decoupling it into two easy-to-solve tasks, i.e., alternatively establishing the robust correspondences across different subjects and interpolating the dense deformation fields based on the detected sparse ...
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A new approach, based on the hierarchical soft correspondence detection, has been presented for significantly improving the speed of our previous HAMMER image registration algorithm. Currently, HAMMER takes a relative long time, e.g., up to 80 minutes, to register two regular sized images using Linux machine (with 2.40GHz CPU and 2-Gbyte memory). This is because the results of correspondence de...
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ژورنال
عنوان ژورنال: Human Brain Mapping
سال: 2011
ISSN: 1065-9471
DOI: 10.1002/hbm.21209