LungRegNet: An unsupervised deformable image registration method for 4D‐CT lung
نویسندگان
چکیده
منابع مشابه
An Unsupervised Learning Model for Deformable Medical Image Registration
We present an efficient learning-based algorithm for deformable, pairwise 3D medical image registration. Current registration methods optimize an energy function independently for each pair of images, which can be timeconsuming for large data. We define registration as a parametric function, and optimize its parameters given a set of images from a collection of interest. Given a new pair of sca...
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Background: Medical image interpolation is recently introduced as a helpful tool to obtain further information via initial available images taken by tomography systems. To do this, deformable image registration algorithms are mainly utilized to perform image interpolation using tomography images.Materials and Methods: In this work, 4DCT thoracic images of five real patients provided by DI...
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Deformable registration is needed for a variety of tasks in establishing the voxel correspondence between respiratory phases. Most registration algorithms assume or imply that the deformation field is smooth and continuous everywhere. However, the lungs are contained within closed invaginated sacs called pleurae and are allowed to slide almost independently along the chest wall. This sliding mo...
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ژورنال
عنوان ژورنال: Medical Physics
سال: 2020
ISSN: 0094-2405,2473-4209
DOI: 10.1002/mp.14065