Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification-Reference-Cited by-同舟云学术

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Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification

Published:2024-09-01 Issue:5 Volume:6 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Hou Benjamin^ORCID,Lee Sungwon^ORCID,Lee Jung-Min^ORCID,Koh Christopher^ORCID,Xiao Jing^ORCID,Pickhardt Perry J.^ORCID,Summers Ronald M.

Funder

National Institutes of Health

Intramural Research Program

Publisher

Radiological Society of North America (RSNA)

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.230601

Reference15 articles.

1. Care of Patients with Ascites

2. Impact of ascites volume on clinical outcomes in ovarian cancer: A cohort study

3. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

4. Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Subcutaneous edema segmentation on abdominal CT using multi-class labels and iterative annotation;International Journal of Computer Assisted Radiology and Surgery;2024-09-14

2. Fluid Intelligence: AI’s Role in Accurate Measurement of Ascites;Radiology: Artificial Intelligence;2024-09-01

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