Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI-Reference-Cited by-同舟云学术

Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI

Published:2019-06-14 Issue:02 Volume:6 Page:1
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Chirra Prathyush¹,Leo Patrick¹,Yim Michael²,Bloch B. Nicolas³,Rastinehad Ardeshir R.⁴,Purysko Andrei⁵,Rosen Mark⁶,Madabhushi Anant¹,Viswanath Satish E.¹

Affiliation:

1. Case Western Reserve University, Department of Biomedical Engineering, Cleveland, Ohio

2. Northeast Ohio Medical University, College of Medicine, Rootstown, Ohio

3. Boston University School of Medicine, Department of Radiology, Boston, Massachusetts

4. Icahn School of Medicine at Mount Sinai, Department of Urology, New York, New York

5. Cleveland Clinic, Department of Radiology, Cleveland, Ohio

6. Hospital of the University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

Reference51 articles.

1. Radiomics: the process and the challenges

2. The Potential of Radiomic-Based Phenotyping in Precision Medicine

3. Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures

4. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

5. A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme

Cited by 32 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. Radiomic study of antenatal prediction of severe placenta accreta spectrum from MRI;British Journal of Radiology;2024-08-17

2. Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA;Neuroinformatics;2024-06-11

3. Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study;Medical & Biological Engineering & Computing;2024-03-27

4. A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation;IEEE Access;2024

5. Radiotherapy outcome prediction with medical imaging;Machine Learning and Artificial Intelligence in Radiation Oncology;2024