Pseudo CT Estimation from MRI Using Patch-based Random Forest - PMC
www.ncbi.nlm.nih.gov › PMC6788808
We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the ...
This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.
Estimating ct image from mri data using structured random forest and auto-context model ... Pseudo ct estimation from mri using patch-based random forest. Medical ...
A Conditional Inference Random Forest (CIRF) modelled the relation between MRI descriptors and CT patches. For validation, test images were spatially normalized ...
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Apr 5, 2019 · An auto-context model with patch-based anatomical features was integrated into a classification random forest to generate and improve semantic ...
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Abstract—Dose calculation from MRI is a topical issue. New treatment systems combining a linear accelerator with a MRI have been recently being developed.
A novel learning-based approach to automatically generate CT images from routine T1-weighted MR images based on a random forest regression with patch-based ...
Oct 1, 2021 · AbstractIn recent years, research has been showing a great interest in using magnetic resonance imaging (MRI) as the only modality for ...
We propose a method for pseudo CT estimation from MR images based on joint dictionary learning. Patient-specific anatomical features were extracted from the ...
We propose a method to generate patient-specific pseudo CT (pCT) from routinely-acquired MRI based on semantic information-based random forest and ...