ArticleJournal of medical imaging (Bellingham, Wash.)2017
Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography.
Article in Journal of medical imaging (Bellingham, Wash.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Joint EANM/SNMMI guideline on radiomics in nuclear medicine : Jointly supported by the EANM Physics Committee and the SNMMI Physics, Instrumentation and Data Sciences Council.European journal of nuclear medicine and molecular imaging · 2023Guideline
- Extending Regression Without Truth to Integrate Ground-Truth Measurements for Evaluating Quantitative Imaging Methods with Patient Data.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Comparing evaluation of quantitative imaging methods using reference standards versus regression‑without‑truth‑based technique.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Need for Objective Task-Based Evaluation of Image Segmentation Algorithms for Quantitative PET: A Study with ACRIN 6668/RTOG 0235 Multicenter Clinical Trial Data.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- How accurately can quantitative imaging methods be ranked without ground truth: An upper bound on no-gold-standard evaluation.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Carotid atherosclerotic plaque segmentation in multi-weighted MRI using a two-stage neural network: advantages of training with high-resolution imaging and histology.Frontiers in cardiovascular medicine · 2023Article
- Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines).Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- A tissue-fraction estimation-based segmentation method for quantitative dopamine transporter SPECT.Medical physics · 2022Article
- A Bayesian approach to tissue-fraction estimation for oncological PET segmentation.Physics in medicine and biology · 2021Article
- A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.Physics in medicine and biology · 2020Article
- Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images.Journal of medical imaging (Bellingham, Wash.) · 2017Article
- No-gold-standard evaluation of image-acquisition methods using patient data.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise.Proceedings of SPIE--the International Society for Optical EngineeringArticle
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.