Maailman ylikulutuspäivä on täällä taas – loppuvuosi eletään velaksi https://wwf.fi/uutiset/2026/07/maailman-ylikulutuspaiva-on-taalla-taas-loppuvuosi-eletaan-velaksi/
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Predictive Enhancement Calibration for Latent Breast MRI Virtual Contrast Enhancement
Qin Lei, Hao Wu
https://arxiv.org/abs/2608.03612 https://arxiv.org/pdf/2608.03612 https://arxiv.org/html/2608.03612
arXiv:2608.03612v1 Announce Type: new
Abstract: Virtual contrast enhancement (VCE) synthesizes enhanced breast MR images from pre-contrast acquisitions. Modern latent generators offer strong image priors, but their bounded natural-image autoencoders conflict with the non-canonical intensity scale of MRI. We show that the upper bound can alter radiomic fidelity before generation, while scaling source and target independently creates a coordinate inconsistency. We propose Predictive Enhancement Calibration (PEC), which represents each pair in a shared, case-adaptive coordinate during training and predicts its unavailable upper endpoint from the pre-contrast image at inference. We integrate PEC with a pretrained FLUX latent flow transformer via parameter-efficient reference conditioning. Target round trips first isolate representation loss before generation; near-matched conditional models then compare PEC with fixed-wide and separate coordinates under comparable training budgets and backbone settings. On the fixed internal MAMA100 development cohort, PEC improves all eight point estimates in this source-only VCE setting, with paired evidence strongest for MSE and LPIPS.\noindent\textbf{Code:} https://github.com/tanlei0/pec-breast-mri-vce
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Kerro kyselyssä, miten parantaisit Helsingin katuja ja puistoja – arvomme palkintoja https://www.hel.fi/fi/uutiset/kerro-kyselyssa-miten-parantaisit-helsingin-katuja-ja-puistoja-arvomme-palkintoja
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