ArticleMedical image analysis2021
Data-Driven multi-Contrast spectral microstructure imaging with InSpect: INtegrated SPECTral component estimation and mapping.
Article in Medical image analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Roles and applications of artificial intelligence in fetal and placental MRI: a literature review.BMC pregnancy and childbirth · 2026Pooled it
- Diffusion-relaxation MRI as virtual histology: separable microstructural signatures of AD pathology in ex vivo human brain.Research square · 2026Article
- Separable multidimensional MRI signatures of cellular and structural pathology in Alzheimer's disease.bioRxiv : the preprint server for biology · 2026Article
- HERON: High-Efficiency Real-Time Motion Quantification and Re-Acquisition for Fetal Diffusion MRI.IEEE transactions on medical imaging · 2025Article
- Placental multimodal MRI prior to spontaneous preterm birth <32 weeks' gestation: An observational study.BJOG : an international journal of obstetrics and gynaecology · 2024Observational
- Advanced magnetic resonance imaging detects altered placental development in pregnancies affected by congenital heart disease.Scientific reports · 2024Article
- Preeclampsia Associated Differences in the Placenta, Fetal Brain, and Maternal Heart Can Be Demonstrated Antenatally: An Observational Cohort Study Using MRI.Hypertension (Dallas, Tex. : 1979) · 2024Observational
- Advanced magnetic resonance imaging detects altered placental development in pregnancies affected by congenital heart disease.Research square · 2024Article
- Non-invasive mapping of human placenta microenvironments throughout pregnancy with diffusion-relaxation MRI.Placenta · 2023Article
- Assessing within-subject rates of change of placental MRI diffusion metrics in normal pregnancy.Magnetic resonance in medicine · 2023Article
- Low-Field Combined Diffusion-Relaxation MRI for Mapping Placenta Structure and Function.medRxiv : the preprint server for health sciences · 2023Article
- Multi-modal MRI reveals changes in placental function following preterm premature rupture of membranes.Magnetic resonance in medicine · 2023Article
- Loss of aquaporin-4 results in glymphatic system dysfunction via brain-wide interstitial fluid stagnation.eLife · 2023Article
- Mapping the individual human cortex using multidimensional MRI and unsupervised learning.Brain communications · 2023Article
- In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods.Applied magnetic resonance · 2023Article
- Dynamics of T2* and deformation in the placenta and myometrium during pre-labour contractions.Scientific reports · 2022Article
- Data-Driven multi-Contrast spectral microstructure imaging with InSpect: INtegrated SPECTral component estimation and mapping.Medical image analysis · 2021Article
- Multidimensional MRI for Characterization of Subtle Axonal Injury Accelerated Using an Adaptive Nonlocal Multispectral Filter.Frontiers in physics · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
We introduce and demonstrate an unsupervised machine learning technique for spectroscopic analysis of quantitative MRI experiments. Our algorithm supports estimation of one-dimensional spectra from single-contrast data, and multidimensional correlation spectra from simultaneous multi-contrast data. These spectrum-based approaches allow model-free investigation of tissue properties, but require regularised inversion of a Laplace transform or Fredholm integral, which is an ill-posed calculation. Here we present a method that addresses this limitation in a data-driven way. The algorithm simultaneously estimates a canonical basis of spectral components and voxelwise maps of their weightings, thereby pooling information across whole images to regularise the ill-posed problem. We show in simulations that our algorithm substantially outperforms current voxelwise spectral approaches. We demonstrate the method on multi-contrast diffusion-relaxometry placental MRI scans, revealing anatomically-relevant sub-structures, and identifying dysfunctional placentas. Our algorithm vastly reduces the data required to reliably estimate spectra, opening up the possibility of quantitative MRI spectroscopy in a wide range of new applications. Our InSpect code is available at github.com/paddyslator/inspect.
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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.