Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses-Reference-Cited by-同舟云学术

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Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses

Published:2023 Issue: Volume:4 Page:67-76
ISSN:2644-1276
Container-title:IEEE Open Journal of Engineering in Medicine and Biology
language:
Short-container-title:IEEE Open J. Eng. Med. Biol.

Author:

Panic Jovana¹^ORCID,Defeudis Arianna²^ORCID,Balestra Gabriella³^ORCID,Giannini Valentina²^ORCID,Rosati Samanta³^ORCID

Affiliation:

1. Department of Surgical Science, and Polytechnic of Turin, Department of Electronics and Telecommunications, University of Turin, Turin, Italy

2. Department of Surgical Science, University of Turin, Turin, Italy

3. Department of Electronics and Telecommunications, Polytechnic of Turin, Turin, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/8782705/10092241/10111498.pdf?arnumber=10111498

Reference100 articles.

1. MRI-based automatic segmentation of rectal cancer using 2D U-Net on two independent cohorts;knuth;Acta Oncol,2021

2. Are We There Yet? The Value of Deep Learning in a Multicenter Setting for Response Prediction of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy

3. MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

4. A fully automatic deep learning algorithm to segment rectal Cancer on MR images: a multi-center study

5. A field strength independent MR radiomics model to predict pathological complete response in locally advanced rectal cancer

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