Research
Papers & conference acceptances
Peer-reviewed work and accepted abstracts behind QAF, MARF-C, and MARF-S. Drag to explore.
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QAF
Quality Assessment Framework
RSNA 2025
Presented
Development of a universal task-specific image quality assessment framework for Spectral Photon Counting CT – a phantom study
Presented at RSNA 2025 — task-specific IQ assessment for spectral photon-counting CT, foundational work behind QAF.
Launch QAF →MARF-C
Metal Artefact Reduction Framework for Conventional CT
Biomedical Signal Processing and Control
Journal paper
An AMUS-GAN based framework for metal artefact reduction in CT images
Published deep-learning MAR for conventional CT — core research behind MARF-C.
View paper →MARF-C
Metal Artefact Reduction Framework for Conventional CT
IEEE NSS-MIC / RTSD 2026
Abstract accepted
QAF-MAR: A web-based quantitative framework for standardized evaluation of metal artefact reduction in CT
Accepted at IEEE NSS-MIC / RTSD 2026 — standardized, web-based metrics for MAR evaluation.
Launch QAF →MARF-S
Metal Artefact Reduction Framework for Spectral Photon-Counting CT
RSNA 2026
Abstract accepted
Spectral consistency guided semi-supervised metal artefact reduction in photon-counting CT imaging
Accepted for RSNA 2026 — spectral-consistency MAR for photon-counting CT.
Learn more →MARF-S
Metal Artefact Reduction Framework for Spectral Photon-Counting CT
IEEE NSS-MIC / RTSD 2026
Abstract accepted
Metal artefact reduction for quantitative bone and soft-tissue material decomposition in photon-counting CT
Accepted at IEEE NSS-MIC / RTSD 2026 — MAR that preserves quantitative material decomposition.
Learn more →QAF
Quality Assessment Framework
RSNA 2025
Presented
Development of a universal task-specific image quality assessment framework for Spectral Photon Counting CT – a phantom study
Presented at RSNA 2025 — task-specific IQ assessment for spectral photon-counting CT, foundational work behind QAF.
Launch QAF →MARF-C
Metal Artefact Reduction Framework for Conventional CT
Biomedical Signal Processing and Control
Journal paper
An AMUS-GAN based framework for metal artefact reduction in CT images
Published deep-learning MAR for conventional CT — core research behind MARF-C.
View paper →MARF-C
Metal Artefact Reduction Framework for Conventional CT
IEEE NSS-MIC / RTSD 2026
Abstract accepted
QAF-MAR: A web-based quantitative framework for standardized evaluation of metal artefact reduction in CT
Accepted at IEEE NSS-MIC / RTSD 2026 — standardized, web-based metrics for MAR evaluation.
Launch QAF →MARF-S
Metal Artefact Reduction Framework for Spectral Photon-Counting CT
RSNA 2026
Abstract accepted
Spectral consistency guided semi-supervised metal artefact reduction in photon-counting CT imaging
Accepted for RSNA 2026 — spectral-consistency MAR for photon-counting CT.
Learn more →MARF-S
Metal Artefact Reduction Framework for Spectral Photon-Counting CT
IEEE NSS-MIC / RTSD 2026
Abstract accepted
Metal artefact reduction for quantitative bone and soft-tissue material decomposition in photon-counting CT
Accepted at IEEE NSS-MIC / RTSD 2026 — MAR that preserves quantitative material decomposition.
Learn more →Publications
- QAF
M. Alzaabi, A. Behouch, B. Tariq, A. Raja, and N. Maalej, “Power law spectral photon-counting CT for quantitative effective atomic number and electron density imaging,” Phys. Med. Biol., vol. 71, no. 14, p. 145015, Jul. 2026, doi: 10.1088/1361-6560/ae8aab.
Spectral photon-counting CT (SPCCT)Effective atomic numberElectron densityView paper → - QAF
B. Tariq, O. Sikander, N. Francis, M. Alkhatib, F. Naseer, N. Werghi, E. Memisoglu, N. Maalej, and A. Raja, “Assessment of material identification and quantification in the presence of metals using spectral photon counting CT,” PLOS ONE, vol. 19, no. 9, p. e0308658, Sep. 2024, doi: 10.1371/journal.pone.0308658.
Spectral photon-counting CT (SPCCT)Metal artefactsMaterial identification and quantificationView paper → - MARF-S
O. Khan et al., “Development of Residual Dense U-Net (RDU-Net)-Based Metal Artefacts Reduction Technique Using Spectral Photon Counting CT,” in IEEE Access, vol. 12, pp. 109735–109749, 2024, doi: 10.1109/ACCESS.2024.3439861.
Computed tomography (CT)Metal artefacts reduction (MAR)Spectral photon-counting CT (SPCCT)View paper →
Contact
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aamirraja@quantisight.io