1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models
Markus Ditlev Sjøgren Olsen, Jakob Ambsdorf, Manxi Lin +7
Congenital malformations of the brain are among the most common fetal abnormalities that impact fetal development. Previous anomaly detection methods on ultrasound images are based…
Yucca: A Deep Learning Framework For Medical Image Analysis
Sebastian Nørgaard Llambias, Julia Machnio, Asbjørn Munk +3
Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-frien…
Learning semantic image quality for fetal ultrasound from noisy ranking annotation
Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer +9
We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements. Working in fetal ultrasound, where ranking is challenging an…
Benchmarking Faithfulness: Towards Accurate Natural Language Explanations in Vision-Language Tasks
Jakob Ambsdorf
With deep neural models increasingly permeating our daily lives comes a need for transparent and comprehensible explanations of their decision-making. However, most explanation met…