Samuel Budd

Samuel Budd

Imperial College London

H-index: 7

Europe-United Kingdom

About Samuel Budd

Samuel Budd, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of Deep Learning for Medical Imaging.

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

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

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

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?

Sonographer interaction with artificial intelligence: collaboration or conflict?

Symbiotic deep learning for medical image analysis with applications in real-time diagnosis for fetal ultrasound screening

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time

A survey on active learning and human-in-the-loop deep learning for medical image analysis

Prototyping CRISP: a Causal Relation and Inference Search Platform applied to colorectal cancer data

Samuel Budd Information

University

Position

PhD Candidate

Citations(all)

486

Citations(since 2020)

485

Cited By

27

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Imperial College London

Google Scholar

View Google Scholar Profile

Samuel Budd Skills & Research Interests

Deep Learning for Medical Imaging

Top articles of Samuel Budd

Title

Journal

Author(s)

Publication Date

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

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

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?

Prenatal Diagnosis

Thomas G Day

Samuel Budd

Jeremy Tan

Jacqueline Matthew

Emily Skelton

...

2023/9/30

Sonographer interaction with artificial intelligence: collaboration or conflict?

Ultrasound in Obstetrics and Gynecology

TG Day

J Matthew

S Budd

JV Hajnal

JM Simpson

...

2023/8

Symbiotic deep learning for medical image analysis with applications in real-time diagnosis for fetal ultrasound screening

Samuel Budd

2022

Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time

Jacqueline Matthew

Emily Skelton

Thomas G Day

Veronika A Zimmer

Alberto Gomez

...

2021

A survey on active learning and human-in-the-loop deep learning for medical image analysis

Samuel Budd

Emma C Robinson

Bernhard Kainz

2021/7/1

Prototyping CRISP: a Causal Relation and Inference Search Platform applied to colorectal cancer data

Samuel Budd

Arno Blaas

Adrienne Hoarfrost

Kia Khezeli

Krittika D'Silva

...

2021/3/9

Can non-specialists provide high quality gold standard labels in challenging modalities?

Samuel Budd

Thomas Day

John Simpson

Karen Lloyd

Jacqueline Matthew

...

2021

Federated causal inference for out-of-distribution generalization in predicting physiological effects of radiation exposure

AGU Fall Meeting Abstracts

Lauren Sanders

Paul Duckworth

Odhran O'Donoghue

Linus Scheibenreif

Giuseppe Ughi

...

2021/12

Detecting hypo-plastic left heart syndrome in fetal ultrasound via disease-specific atlas maps

Samuel Budd

Matthew Sinclair

Thomas Day

Athanasios Vlontzos

Jeremy Tan

...

2021

Invariant risk minimisation for cross-organism inference: substituting mouse data for human data in human risk factor discovery

arXiv preprint arXiv:2111.07348

Odhran O'Donoghue

Paul Duckworth

Giuseppe Ughi

Linus Scheibenreif

Kia Khezeli

...

2021/11/14

VP17. 01: Exploring a new paradigm for the fetal anomaly ultrasound scan: artificial intelligence in real‐time.

Ultrasound in Obstetrics & Gynecology

J Matthew

E Skelton

T Day

V Zimmer

A Gomez

...

2021/10/2

3D probabilistic segmentation and volumetry from 2D projection images

Athanasios Vlontzos

Samuel Budd

Benjamin Hou

Daniel Rueckert

Bernhard Kainz

2020

Surface agnostic metrics for cortical volume segmentation and regression

Samuel Budd

Prachi Patkee

Ana Baburamani

Mary Rutherford

Emma C Robinson

...

2020

See List of Professors in Samuel Budd University(Imperial College London)

Co-Authors

H-index: 132
Daniel Rueckert

Daniel Rueckert

Technische Universität München

H-index: 46
Bernhard Kainz

Bernhard Kainz

Imperial College London

H-index: 30
Emma C. Robinson

Emma C. Robinson

King's College London

H-index: 26
Matthew Sinclair

Matthew Sinclair

Imperial College London

H-index: 22
Alberto Gomez

Alberto Gomez

King's College

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