In vivo variability of MRI radiomics features in prostate lesions assessed by a test-retest study with repositioning
Abstract Despite academic success, radiomics-based machine learning algorithms have not reached clinical practice, partially due to limited repeatability/reproducibility. To address this issue, this work aims to identify a stable subset of radiomics features in prostate MRI for radiomics modelling....
Saved in:
| Main Authors: | Kevin Sun Zhang, Christian Jan Oliver Neelsen, Markus Wennmann, Thomas Hielscher, Balint Kovacs, Philip Alexander Glemser, Magdalena Görtz, Albrecht Stenzinger, Klaus H. Maier-Hein, Johannes Huber, Heinz-Peter Schlemmer, David Bonekamp |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-09989-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Open-radiomics: a collection of standardized datasets and a technical protocol for reproducible radiomics machine learning pipelines
by: Khashayar Namdar, et al.
Published: (2025-08-01) -
A study on the repeatability of radiomics parameters under repeated CT scans
by: Yi-Zhi Zhao, et al.
Published: (2025-07-01) -
Addressing Multi-Center Variability in Radiomic Analysis: A Comparative Study of Image Acquisition Methods Across Two 3T MRI Scanners
by: Claudia Tocilă-Mătășel, et al.
Published: (2025-02-01) -
A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights
by: Muna Alsallal, et al.
Published: (2025-05-01) -
Improving risk stratification of PI-RADS 3 + 1 lesions of the peripheral zone: expert lexicon of terms, multi-reader performance and contribution of artificial intelligence
by: Philip A. Glemser, et al.
Published: (2025-08-01)