March 14, 2024, 4:42 a.m. | Paraskevas Pegios, Manxi Lin, Nina Weng, Morten Bo S{\o}ndergaard Svendsen, Zahra Bashir, Siavash Bigdeli, Anders Nymark Christensen, Martin Tolsgaard

cs.LG updates on

arXiv:2403.08700v1 Announce Type: cross
Abstract: Obstetric ultrasound image quality is crucial for accurate diagnosis and monitoring of fetal health. However, producing high-quality standard planes is difficult, influenced by the sonographer's expertise and factors like the maternal BMI or the fetus dynamics. In this work, we propose using diffusion-based counterfactual explainable AI to generate realistic high-quality standard planes from low-quality non-standard ones. Through quantitative and qualitative evaluation, we demonstrate the effectiveness of our method in producing plausible counterfactuals of increased quality. …

abstract arxiv assessment bmi counterfactual cs.hc cs.lg diagnosis diffusion dynamics eess.iv expertise health however image iterative monitoring planes quality standard type work

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