Aasa Feragen

Aasa Feragen

Danmarks Tekniske Universitet

H-index: 18

Europe-Denmark

About Aasa Feragen

Aasa Feragen, With an exceptional h-index of 18 and a recent h-index of 16 (since 2020), a distinguished researcher at Danmarks Tekniske Universitet, specializes in the field of Machine learning, medical imaging, geometric modelling.

His recent articles reflect a diverse array of research interests and contributions to the field:

AI supported fetal echocardiography with quality assessment

Populations of unlabelled networks: Graph space geometry and generalized geodesic principal components

Deployment of Deep Learning Model in Real World Clinical Setting: A Case Study in Obstetric Ultrasound

Learning semantic image quality for fetal ultrasound from noisy ranking annotation

Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment

Role of AI‐assisted automated cardiac biometrics in screening for fetal coarctation of aorta

Non-discrimination Criteria for Generative Language Models

Interpreting Equivariant Representations

Aasa Feragen Information

University

Position

Professor, DTU Compute

Citations(all)

1365

Citations(since 2020)

902

Cited By

752

hIndex(all)

18

hIndex(since 2020)

16

i10Index(all)

35

i10Index(since 2020)

27

Email

University Profile Page

Danmarks Tekniske Universitet

Google Scholar

View Google Scholar Profile

Aasa Feragen Skills & Research Interests

Machine learning

medical imaging

geometric modelling

Top articles of Aasa Feragen

Title

Journal

Author(s)

Publication Date

AI supported fetal echocardiography with quality assessment

Scientific Reports

Caroline A Taksoee-Vester

Kamil Mikolaj

Zahra Bashir

Anders N Christensen

Olav B Petersen

...

2024/3/9

Populations of unlabelled networks: Graph space geometry and generalized geodesic principal components

Biometrika

Anna Calissano

Aasa Feragen

Simone Vantini

2024/3/1

Deployment of Deep Learning Model in Real World Clinical Setting: A Case Study in Obstetric Ultrasound

arXiv preprint arXiv:2404.00032

Chun Kit Wong

Mary Ngo

Manxi Lin

Zahra Bashir

Amihai Heen

...

2024/3/22

Learning semantic image quality for fetal ultrasound from noisy ranking annotation

arXiv preprint arXiv:2402.08294

Manxi Lin

Jakob Ambsdorf

Emilie Pi Fogtmann Sejer

Zahra Bashir

Chun Kit Wong

...

2024/2/13

Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment

arXiv preprint arXiv:2403.08700

Paraskevas Pegios

Manxi Lin

Nina Weng

Morten Bo Søndergaard Svendsen

Zahra Bashir

...

2024/3/13

Role of AI‐assisted automated cardiac biometrics in screening for fetal coarctation of aorta

Ultrasound in Obstetrics & Gynecology

CA Taksoee‐Vester

K Mikolaj

OBB Petersen

NG Vejlstrup

AN Christensen

...

2024/2/9

Non-discrimination Criteria for Generative Language Models

arXiv preprint arXiv:2403.08564

Sara Sterlie

Nina Weng

Aasa Feragen

2024/3/13

Interpreting Equivariant Representations

arXiv preprint arXiv:2401.12588

Andreas Abildtrup Hansen

Anna Calissano

Aasa Feragen

2024/1/23

Shortcut Learning in Medical Image Segmentation

arXiv preprint arXiv:2403.06748

Manxi Lin*

Nina Weng*

Kamil Mikolaj

Zahra Bashir

Morten Bo Søndergaard Svendsen

...

2024/3/11

Kære minister, forestil dig et fremtidsscenario, hvor du går ned med stress

Politiken

Aasa Feragen

Melanie Ganz-Benjaminsen

Sune Hannibal Holm

2023

Are demographically invariant models and representations in medical imaging fair?

arXiv preprint arXiv:2305.01397

Eike Petersen

Enzo Ferrante

Melanie Ganz

Aasa Feragen

2023/5/2

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv preprint arXiv:2309.12325

Karim Lekadir

Aasa Feragen

Abdul Joseph Fofanah

Alejandro F Frangi

Alena Buyx

...

2023/8/11

Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation

arXiv preprint arXiv:2312.14223

Nina Weng

Paraskevas Pegios

Aasa Feragen

Eike Petersen

Siavash Bigdeli

2023/12/21

That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation

arXiv preprint arXiv:2303.15850

Kilian Zepf

Eike Petersen

Jes Frellsen

Aasa Feragen

2023/3/28

The path toward equal performance in medical machine learning

Eike Petersen

Sune Holm

Melanie Ganz

Aasa Feragen

2023/7/14

Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging: 12th International Workshop, CLIP 2023 1st …

Stefan Wesarg

Esther Puyol Antón

John SH Baxter

Marius Erdt

Klaus Drechsler

...

2023/10/9

Removing confounding information from fetal ultrasound images

arXiv preprint arXiv:2303.13918

Kamil Mikolaj

Manxi Lin

Zahra Bashir

Morten Bo Søndergaard Svendsen

Martin Tolsgaard

...

2023/3/24

On (assessing) the fairness of risk score models

Eike Petersen

Melanie Ganz

Sune Holm

Aasa Feragen

2023/6/12

Are Sex-Based Physiological Differences the Cause of Gender Bias for Chest X-Ray Diagnosis?

Nina Weng

Siavash Bigdeli

Eike Petersen

Aasa Feragen

2023/10/8

Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty

arXiv preprint arXiv:2303.13123

Kilian Zepf

Selma Wanna

Marco Miani

Juston Moore

Jes Frellsen

...

2023/3/23

See List of Professors in Aasa Feragen University(Danmarks Tekniske Universitet)

Co-Authors

H-index: 57
Marleen de Bruijne

Marleen de Bruijne

Københavns Universitet

H-index: 45
Mads Nielsen

Mads Nielsen

Københavns Universitet

H-index: 30
Søren Hauberg

Søren Hauberg

Danmarks Tekniske Universitet

H-index: 24
Simone Vantini

Simone Vantini

Politecnico di Milano

H-index: 20
Jens Petersen

Jens Petersen

Københavns Universitet

H-index: 14
Matthew Liptrot

Matthew Liptrot

Københavns Universitet

academic-engine