Bernhard Kainz

Bernhard Kainz

Imperial College London

H-index: 46

Europe-United Kingdom

About Bernhard Kainz

Bernhard Kainz, With an exceptional h-index of 46 and a recent h-index of 42 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of human-in-the-loop computing, machine learning, medical image analysis.

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

DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection

Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases

Remote Expert DVT Triaging of Novice-User Compression Sonography with AI-Guidance

Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentation

Whole-examination AI estimation of fetal biometrics from 20-week ultrasound scans

Automatic Segmentation of Lymphatic Perfusion in Patients with Congenital Single Ventricle Defects

Bernhard Kainz Information

University

Position

___

Citations(all)

16052

Citations(since 2020)

14607

Cited By

4957

hIndex(all)

46

hIndex(since 2020)

42

i10Index(all)

110

i10Index(since 2020)

98

Email

University Profile Page

Imperial College London

Google Scholar

View Google Scholar Profile

Bernhard Kainz Skills & Research Interests

human-in-the-loop computing

machine learning

medical image analysis

Top articles of Bernhard Kainz

Title

Journal

Author(s)

Publication Date

DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection

Proceedings/IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging

Sergio Naval Marimont

Matthew Baugh

Vasilis Siomos

Christos Tzelepis

Bernhard Kainz

...

2024/2/2

Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases

arXiv preprint arXiv:2403.16776

Sophie Starck

Vasiliki Sideri-Lampretsa

Bernhard Kainz

Martin Menten

Tamara Mueller

...

2024/3/25

Remote Expert DVT Triaging of Novice-User Compression Sonography with AI-Guidance

Annals of Vascular Surgery

Jonas Oppenheimer

Ramin Mandegaran

Finja Staabs

Andrea Adler

Stephan Singöhl

...

2024/2/1

Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability

Proceedings of the AAAI Conference on Artificial Intelligence

Mischa Dombrowski

Hadrien Reynaud

Johanna P Müller

Matthew Baugh

Bernhard Kainz

2024/3/24

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

Ultrasound in Obstetrics & Gynecology

TG Day

J Matthew

SF Budd

L Venturini

R Wright

...

2024/1/10

Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentation

arXiv preprint arXiv:2403.14429

Mathias Öttl

Frauke Wilm

Jana Steenpass

Jingna Qiu

Matthias Rübner

...

2024/3/21

Whole-examination AI estimation of fetal biometrics from 20-week ultrasound scans

arXiv preprint arXiv:2401.01201

Lorenzo Venturini

Samuel Budd

Alfonso Farruggia

Robert Wright

Jacqueline Matthew

...

2024/1/2

Automatic Segmentation of Lymphatic Perfusion in Patients with Congenital Single Ventricle Defects

Marietta Stegmaier

Johanna P Müller

Christian Schröder

Thomas Day

Michela Cuomo

...

2024/2/20

Understanding metric-related pitfalls in image analysis validation

Annika Reinke

Minu D Tizabi

Michael Baumgartner

Matthias Eisenmann

Doreen Heckmann-Nötzel

...

2024/2/12

Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks

Matthew Baugh

Jeremy Tan

Johanna P Müller

Mischa Dombrowski

James Batten

...

2023/10/1

Sculpting Efficiency: Pruning Medical Imaging Models for On-Device Inference

arXiv preprint arXiv:2309.05090

Sudarshan Sreeram

Bernhard Kainz

2023/9/10

Confidence-Aware and Self-supervised Image Anomaly Localisation

Johanna P. Müller

Matthew Baugh

Jeremy Tan

Mischa Dombrowski

Bernhard Kainz

2023/10/7

Estimating categorical counterfactuals via deep twin networks

Nature Machine Intelligence

Athanasios Vlontzos

Bernhard Kainz

Ciarán M Gilligan-Lee

2023/2

BORS/BJR TRAVELLING FELLOWSHIP ABSTRACT: MOTION CAPTURE OF NEONATAL INFANT KICKING MOVEMENTS CAN PROVIDE AN EARLY PREDICTION OF CEREBRAL PALSY

Orthopaedic Proceedings

Nidal Khatib

Luca Schmidtke

Anna Lukens

Tomoki Arichi

Niamh Nowlan

...

2023/11/17

Improving image labelling quality

Nature Machine Intelligence

Thomas G Day

John M Simpson

Reza Razavi

Bernhard Kainz

2023/4

Zero-shot anomaly detection with pre-trained segmentation models

arXiv preprint arXiv:2306.09269

Matthew Baugh

James Batten

Johanna P Müller

Bernhard Kainz

2023/6/15

Feature-conditioned cascaded video diffusion models for precise echocardiogram synthesis

Hadrien Reynaud

Mengyun Qiao

Mischa Dombrowski

Thomas Day

Reza Razavi

...

2023/10/1

Blood vessel obstruction diagnosis apparatus

2023/9/6

Robust Segmentation via Topology Violation Detection and Feature Synthesis

Liu Li

Qiang Ma

Cheng Ouyang

Zeju Li

Qingjie Meng

...

2023/10/1

Exploring the Hyperparameter Space of Image Diffusion Models for Echocardiogram Generation

arXiv preprint arXiv:2311.01567

Hadrien Reynaud

Bernhard Kainz

2023/11/2

See List of Professors in Bernhard Kainz University(Imperial College London)

Co-Authors

H-index: 132
Daniel Rueckert

Daniel Rueckert

Technische Universität München

H-index: 104
Jo Hajnal

Jo Hajnal

King's College

H-index: 99
mary rutherford

mary rutherford

King's College

H-index: 83
Dieter Schmalstieg

Dieter Schmalstieg

Technische Universität Graz

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