arXiv AI October 15, 2026 By Ammar Bhilwarawala, Mainak Bandyopadhyay

FETALFusion: Resolution-Aware State-Space Modeling for Multi-Domain Fetal Head Segmentation

FETALFusion is a dual‑path CNN‑Mamba encoder‑decoder designed for fetal head segmentation in 2D ultrasound across transabdominal and transperineal acquisition types. It uses four‑directional state‑space scans at the highest‑resolution stages, domain‑specific channel gates, and a weak landmark shape prior, achieving a Dice score of 0.963 and an HD95 of 2.10 mm on a held‑out test set of 471 images. Ablation studies show that the landmark prior and domain gates drive most of the performance gains, while the state‑space branch has minimal impact. whyItMatters":"The method provides highly accurate fetal head segmentation without test‑time augmentation or domain labels, enabling reliable head circumference measurement for monitoring fetal growth."

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 AI.

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llms agents computer-vision fine-tuning efficiency multimodal safety

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Anatomy-Guided Foundation Model Adaptation with Within-Case Prototype Supervision for Standard Plane Detection in Fetal Ultrasound Blind Sweeps

FUSEP: A Multi-Center Benchmark for Diverse Tasks in Early Pregnancy Fetal Ultrasound Screening

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Beyond In-Distribution Metrics: A Systematic Out-of-Distribution Evaluation of Congenital Heart Disease Segmentation