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pro vyhledávání: '"Green, Andrew F."'
The aim of this study was to develop a model to accurately identify corresponding points between organ segmentations of different patients for radiotherapy applications. A model for simultaneous correspondence and interpolation estimation in 3D shape
Externí odkaz:
http://arxiv.org/abs/2309.14269
Generalised Automatic Anatomy Finder (GAAF): A general framework for 3D location-finding in CT scans
We present GAAF, a Generalised Automatic Anatomy Finder, for the identification of generic anatomical locations in 3D CT scans. GAAF is an end-to-end pipeline, with dedicated modules for data pre-processing, model training, and inference. At it's cor
Externí odkaz:
http://arxiv.org/abs/2209.06042
Abdominal organ segmentation is a difficult and time-consuming task. To reduce the burden on clinical experts, fully-automated methods are highly desirable. Current approaches are dominated by Convolutional Neural Networks (CNNs) however the computat
Externí odkaz:
http://arxiv.org/abs/2207.10446
Automatic segmentation of organs-at-risk (OARs) in CT scans using convolutional neural networks (CNNs) is being introduced into the radiotherapy workflow. However, these segmentations still require manual editing and approval by clinicians prior to c
Externí odkaz:
http://arxiv.org/abs/2206.13317
Publikováno v:
In Physics and Imaging in Radiation Oncology April 2022 22:44-50
Akademický článek
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