Deep Learning–based Automatic Lung Segmentation on Multiresolution CT Scans from Healthy and Fibrotic Lungs in Mice-Reference-Cited by-同舟云学术

Deep Learning–based Automatic Lung Segmentation on Multiresolution CT Scans from Healthy and Fibrotic Lungs in Mice

Published:2022-03-01 Issue:2 Volume:4 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Sforazzini Francesco^ORCID,Salome Patrick^ORCID,Moustafa Mahmoud,Zhou Cheng,Schwager Christian^ORCID,Rein Katrin,Bougatf Nina^ORCID,Kudak Andreas^ORCID,Woodruff Henry^ORCID,Dubois Ludwig^ORCID,Lambin Philippe^ORCID,Debus Jürgen,Abdollahi Amir,Knoll Maximilian^ORCID

Funder

European Research Council

European Union

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.210095

Reference14 articles.

1. Quantitative assessment of radiation dose and fractionation effects on normal tissue by utilizing a novel lung fibrosis index model

2. Atlas-based whole-body segmentation of mice from low-contrast Micro-CT data

3. A Novel Mouse Segmentation Method Based on Dynamic Contrast Enhanced Micro-CT Images

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