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arXiv Computer Vision By Jonghun Kim, Junmo Kwon, Hyunjin Park

Mixture of Multi-Sequence Feature Difference for Contrast-Enhanced MRI Synthesis

Read the original on arXiv Computer Vision →

The paper presents a method for synthesizing contrast‑enhanced MRI (CE‑MRI) from non‑contrast sequences using a novel Mixture of Feature Difference (MoFD) module. MoFD dynamically weights and aggregates features from individual sequences and their explicit differences, improving image fidelity and perceptual quality over baseline approaches. Experiments on UCSF‑PDGM and UPenn‑GBM datasets show that the synthesized images reconstruct tumor regions well and yield segmentation performance comparable to real CE‑MRI, with regression‑based training achieving higher structural fidelity.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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