Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 46 min ago
Peer-reviewedCC BYNuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

What approach to brain partial volume correction is best for PET/MRI?

Abstract

Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms.

Related

  1. Quantum metrology via partial quantum error correction
    Yinan Chen, Zongyuan Wang, Sisi Zhou
    arXivPreprintarXiv licenceFull textQuantum physics & quantum informationarXiv
  2. What Must Survive? Exact Task-Information--State Frontiers Under Partial Task Revelation
    Ronald Katende
    arXivPreprintCC BY 4.0Full textStatistical & nonlinear physicsarXiv
  3. What Does a Semilocal Machine-Learning Correction Actually Learn? Size-Dependent Errors across Four Parent Functionals
    Abhishek Bhattacharjee, Kishan Kumar Mohanta, Subrata Jana +1
    arXivPreprintarXiv licenceFull textPhysical chemistryCondensed matterarXiv
  4. Partial Multistep Prediction of Chaotic Time Series: What Remains Predictable beyond the Horizon of Predictability?
    Vasilii A. Gromov, Maksim Lomakin, Aleksei Kudryashov +1
    arXivPreprintCC BY-NC-ND 4.0Full textStatistical & nonlinear physicsarXiv
  5. The Cross-Substrate Access Assay: What an Indicator Test Must Declare to Travel from Brain to Language Model
    Pieter van Rooyen
    arXivPreprintCC BY 4.0Full textNeuroscienceCondensed matterarXiv
BibTeX
@article{hutton2026what,
  title = {{What approach to brain partial volume correction is best for PET/MRI?}},
  author = {B.F. Hutton and B.A. Thomas and K. Erlandsson and A. Bousse and A. Reilhac-Laborde and D. Kazantsev and S. Pedemonte and K. Vunckx and S.R. Arridge and S. Ourselin},
  journal = {Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment},
  year = {2026},
  month = sep,
  doi = {10.1016/j.nima.2012.07.059},
  url = {https://hal.science/hal-05763781v1},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - What approach to brain partial volume correction is best for PET/MRI?
AU  - B.F. Hutton
AU  - B.A. Thomas
AU  - K. Erlandsson
AU  - A. Bousse
AU  - A. Reilhac-Laborde
AU  - D. Kazantsev
AU  - S. Pedemonte
AU  - K. Vunckx
AU  - S.R. Arridge
AU  - S. Ourselin
PY  - 2026
DA  - 2026/09/25
JO  - Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
DO  - 10.1016/j.nima.2012.07.059
UR  - https://hal.science/hal-05763781v1
AB  - Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms.
SN  - 0168-9002
SN  - 1872-9576
ER  -