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20162026
most citedInterpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis

51 citations · 58 across the 10 of their papers we have counts for

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Showing eess.IVShow all

5 papers · 1 filter

eess.IV2025

Temporal Representation Learning for Real-Time Ultrasound Analysis

Yves Stebler, Thomas M. Sutter, Ece Ozkan +1

Ultrasound (US) imaging is a critical tool in medical diagnostics, offering real-time visualization of physiological processes. One of its major advantages is its ability to captur…

eess.IV2025

From Slices to Structures: Unsupervised 3D Reconstruction of Female Pelvic Anatomy from Freehand Transvaginal Ultrasound

Max Krähenmann, Sergio Tascon-Morales, Fabian Laumer +2

Volumetric ultrasound has the potential to significantly improve diagnostic accuracy and clinical decision-making, yet its widespread adoption remains limited by dependence on spec…

eess.IV2025

Predicting Pulmonary Hypertension in Newborns: A Multi-view VAE Approach

Lucas Erlacher, Samuel Ruipérez-Campillo, Holger Michel +4

Pulmonary hypertension (PH) in newborns is a critical condition characterized by elevated pressure in the pulmonary arteries, leading to right ventricular strain and heart failure.…

eess.IV2023

M(otion)-mode Based Prediction of Ejection Fraction using Echocardiograms

Ece Ozkan, Thomas M. Sutter, Yurong Hu +2

Early detection of cardiac dysfunction through routine screening is vital for diagnosing cardiovascular diseases. An important metric of cardiac function is the left ventricular ej…

eess.IV2022★ 1 cited

Interpretable Prediction of Pulmonary Hypertension in Newborns using Echocardiograms

Hanna Ragnarsdottir, Laura Manduchi, Holger Michel +4

Pulmonary hypertension (PH) in newborns and infants is a complex condition associated with several pulmonary, cardiac, and systemic diseases contributing to morbidity and mortality…