Review

Seeing the Risk in Virtual Fat-Suppressed Spine MRI: External Benchmarking and Uncertainty-Guided Selective Risk Analysis.

Zeng-Han Zhou Ying-Ying Song Rong-Rong Liu Xiao-Lu Cao Zong-Yan Jiang Hui Lu Dai-Xiang Jiang Yuan-Feng Liu Xiao-Qing Li

Sep 2026 · Journal of imaging informatics in medicine · 0 citations · 23 references

Medicine

TL;DR

Virtual fat-suppressed MRI is best positioned as uncertainty-guided auxiliary information for selective review, not replacement imaging.

DOI PubMed Semantic Scholar

View source

Similar papers

#artificial intelligence Preprint Sep 2026

GateSPINE: Gated Cross-View Fusion for Lumbar Spine MRI Report Generation

GateSPINE is a vision-language framework that fuses sagittal T1 and T2 volumes with a training-free operator, encodes the fused sagittal and axial volumes with two parallel 3D encoders, and decodes their combined representation into a report, and achieves the highest CE F1 on all three datasets.

Van Nguyen Hoang, Cuong Vuong Tuan, Trang Mai Xuan et al. · 0 citations

Review Aug 2026

Evaluating the Safety of Deep Learning-Based Brain MRI Reconstruction

Objective: Deep learning accelerates brain MRI four- to tenfold, but models can erase lesions or synthesize false tissue - failures pixel-averaged metrics like PSNR and SSIM miss. We review whether current evaluation practices detect this blind spot. Methods: Following PRISMA 2020, we searched seven databases without d...

D. Mai, Thai Viet Pham, Thu Nguyen Thi Dang et al. · 0 citations

Open access Sep 2026

STRESS TESTING SPATIAL ROUTING OF SYNTHESISED T1CE FOR MISSING-MODALITY BRAIN-TUMOUR SEGMENTATION USING TWO-DIMENSIONAL PROCEDURAL PHANTOMS

Apparent gains from adaptive fusion of synthesised contrast-enhanced T1-weighted (T1ce) MRI may reflect unequal label budgets, global calibration, or meta-model flexibility rather than genuinely spatial routing. We stress-tested this mechanism in two separately locked 16-seed studies using procedural phantoms and a 32-...

Zahraa S. Abd-Al Ameer · International Journal of Sci... · 0 citations

Preprint Sep 2026

Anatomically Faithful Artifact Suppression in SENSE Accelerated Brain MRI

It is suggested that ART-Net may support accelerated brain MRI by improving image fidelity and enabling reliable downstream anatomical analysis by improving image fidelity and enabling reliable downstream anatomical analysis.

Chang-Jing Chai, Bin Huang, Li-Bo Xu et al. · 0 citations

Open access Sep 2026

Evaluation-design effects and reference-CT-defined HU-class errors in brain MRI-to-CT synthesis on SynthRAD2023: a technical note.

To quantify how evaluation design affects brain MRI-to-CT synthesis performance, we analyzed 180 MRI/CT pairs from three centers in the SynthRAD2023 Task 1 dataset. A lightweight 2D U-Net was trained with a common validation-based stopping rule under slice-random, patient-random, center-stratified size-matched patient-...

Tatsuya Hayashi, Shinya Kojima, Norio Hayashi · Radiological Physics and Tec... · 0 citations

Preprint Sep 2026

NIMARC-MRI: Abdominal HASTE Dataset and a Baseline U-Net Exposing the Synthetic-to-Real Gap in Low-Resource Motion Correction

Respiratory motion degrades abdominal T2 HASTE MRI in low- and middle-income countries where vendor motion-correction licenses are unavailable and failed scans are deleted during routine PACS cleanup, precluding supervised training. To address this, we introduce NIMARC-MRI, the first public abdominal MRI dataset from W...

Abdulrazaq A. Zubair, Nafiu Musa Muhammad, S. Krah et al. · 0 citations