8 papers
LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation
Sebastian Aas, Elias Stenhede, Arian Ranjbar
RECIST diameter measurements are widely used for tumor response assessment, but they provide only a limited 2D description of lesion extent. We present LETT-NeXt, a lightweight REC…
Echo-POSED: Geometric Self-Distillation for Echocardiography Guidance
Elias Stenhede, Edvart Grüner Bjerke, Joanna Sulkowska +4
We introduce Echo-POSED, a self-supervised framework for real-time transthoracic echocardiography (TTE) guidance that recommends probe adjustments directly from 2D ultrasound image…
Associations between echocardiographic traits and AI-ECG predictions of heart failure
Elias Stenhede, Eivind Bjørkan Orstad, Torbjørn Omland +2
Artificial intelligence-enabled electrocardiography (AI-ECG) can detect heart failure (HF), including disease not captured by left ventricular ejection fraction (LVEF), but the car…
EchoXFlow: A Beamspace Echocardiography Dataset for Cardiac Motion, Flow, and Function
Elias Stenhede, Joanna Sulkowska, Eivind Bjørkan Orstad +2
We introduce EchoXFlow, a clinical echocardiography dataset for learning from ultrasound in its native acquisition geometry rather than from scan-converted Cartesian videos. Existi…
Biomarker-Based Pretraining for Chagas Disease Screening in Electrocardiograms
Elias Stenhede, Arian Ranjbar
Chagas disease screening via ECGs is limited by scarce and noisy labels in existing datasets. We propose a biomarker-based pretraining approach, where an ECG feature extractor is f…
Lite ENSAM: a lightweight cancer segmentation model for 3D Computed Tomography
Agnar Martin Bjørnstad, Elias Stenhede, Arian Ranjbar
Accurate tumor size measurement is a cornerstone of evaluating cancer treatment response. The most widely adopted standard for this purpose is the Response Evaluation Criteria in S…