Two‐stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra‐reader and inter‐reader reliability at full and reduced radiation dose on an external dataset-Reference-Cited by-同舟云学术

Two‐stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra‐reader and inter‐reader reliability at full and reduced radiation dose on an external dataset

Published:2021-03-16 Issue:5 Volume:48 Page:2468-2481
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Panda Ananya¹,Korfiatis Panagiotis¹,Suman Garima¹,Garg Sushil K.²,Polley Eric C.³,Singh Dhruv P.²,Chari Suresh T.⁴,Goenka Ajit H.¹

Affiliation:

1. Department of Radiology Mayo Clinic 200 First Street SW Rochester MN55905USA

2. Department of Gastroenterology and Hepatology Mayo Clinic 200 First Street SW Rochester MN55905USA

3. Department of Biostatistics Health Sciences Research Mayo Clinic 200 First Street SW Rochester MN55905USA

4. Department of Gastroenterology, Hepatology and Nutrition The University of Texas MD Anderson Cancer Center 1515 Holcombe Blvd Houston TX77030USA

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14782

Reference49 articles.

1. Pancreas volume in health and disease: a systematic review and meta-analysis

2. Differences in pancreatic volume, fat content, and fat density measured by multidetector-row computed tomography according to the duration of diabetes

3. The ageing pancreas: a systematic review of the evidence and analysis of the consequences

4. Harnessing Analytic Morphomics for Early Detection of Pancreatic Cancer

5. Adaptive changes in pancreas post Roux-en-Y gastric bypass induced weight loss

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