Alejandro F Frangi

Alejandro F Frangi

University of Leeds

H-index: 77

Europe-United Kingdom

About Alejandro F Frangi

Alejandro F Frangi, With an exceptional h-index of 77 and a recent h-index of 50 (since 2020), a distinguished researcher at University of Leeds, specializes in the field of medical image computing, computational medicine, in silico trials.

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

Retinal imaging for the assessment of stroke risk: a systematic review

Joint magnetic resonance imaging artifacts and noise reduction on discrete shape space of images

Concurrent Left Ventricular Myocardial Diffuse Fibrosis and Left Atrial Dysfunction Strongly Predict Incident Heart Failure

GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology

Predicting risk of cardiovascular disease using retinal OCT imaging

Deep learning for vision and representation learning

Few-shot learning in diffusion models for generating cerebral aneurysm geometries

Alejandro F Frangi Information

University

Position

Diamond Jubilee Chair and RAEng Chair at the ; Honorary Professor at KU Leuven

Citations(all)

34709

Citations(since 2020)

12769

Cited By

26384

hIndex(all)

77

hIndex(since 2020)

50

i10Index(all)

366

i10Index(since 2020)

228

Email

University Profile Page

University of Leeds

Google Scholar

View Google Scholar Profile

Alejandro F Frangi Skills & Research Interests

medical image computing

computational medicine

in silico trials

Top articles of Alejandro F Frangi

Title

Journal

Author(s)

Publication Date

Retinal imaging for the assessment of stroke risk: a systematic review

Zain Girach

Arni Sarian

Cynthia Maldonado-García

Nishant Ravikumar

Panagiotis I Sergouniotis

...

2024/3/2

Joint magnetic resonance imaging artifacts and noise reduction on discrete shape space of images

Pattern Recognition

Xiangyuan Liu

Zhongke Wu

Xingce Wang

Quansheng Liu

Jose M Pozo

...

2024/4/17

Concurrent Left Ventricular Myocardial Diffuse Fibrosis and Left Atrial Dysfunction Strongly Predict Incident Heart Failure

Cardiovascular Imaging

Mark YZ Wong

Jose D Vargas

Hafiz Naderi

Mihir M Sanghvi

Zahra Raisi-Estabragh

...

2024/1/3

GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation

arXiv preprint arXiv:2402.15239

Fengming Lin

Yan Xia

Michael MacRaild

Yash Deo

Haoran Dou

...

2024/2/23

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology

Nature Machine Intelligence

Rodrigo Bonazzola

Enzo Ferrante

Nishant Ravikumar

Yan Xia

Bernard Keavney

...

2024/3/11

Predicting risk of cardiovascular disease using retinal OCT imaging

arXiv preprint arXiv:2403.18873

Cynthia Maldonado-Garcia

Rodrigo Bonazzola

Enzo Ferrante

Thomas H Julian

Panagiotis I Sergouniotis

...

2024/3/26

Deep learning for vision and representation learning

Arezoo Zakeri

Yan Xia

Nishant Ravikumar

Alejandro F Frangi

2024/1/1

Few-shot learning in diffusion models for generating cerebral aneurysm geometries

Y Deo

F Lin

H Dou

N Cheng

N Ravikumar

...

2024/2/2

Deep segmentation of OCTA for evaluation and association of changes of retinal microvasculature with Alzheimer’s disease and mild cognitive impairment

British Journal of Ophthalmology

Jianyang Xie

Quanyong Yi

Yufei Wu

Yalin Zheng

Yonghuai Liu

...

2024/3/1

A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras

IEEE Transactions on Neural Networks and Learning Systems

Haoran Dou

Seppo Virtanen

Nishant Ravikumar

Alejandro F Frangi

2024/3/19

Deep learning fundamentals

Nishant Ravikumar

Arezoo Zakeri

Yan Xia

Alejandro F Frangi

2024/1/1

Beyond images: an integrative multi-modal approach to chest x-ray report generation

Frontiers in Radiology

Nurbanu Aksoy

Serge Sharoff

Selcuk Baser

Nishant Ravikumar

Alejandro F Frangi

2024/2/15

An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation

arXiv preprint arXiv:2403.06317

Soodeh Kalaie

Andy Bulpitt

Alejandro F Frangi

Ali Gooya

2024/3/10

A Geometric Deep Learning Framework for Generation of Virtual Left Ventricles as Graphs

Soodeh Kalaie

Andrew J Bulpitt

Alejandro F Frangi

Ali Gooya

2024/1/23

Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning

arXiv preprint arXiv:2402.15237

Fengming Lin

Yan Xia

Michael MacRaild

Yash Deo

Haoran Dou

...

2024/2/23

Multiple Teachers-Meticulous Student: A Domain Adaptive Meta-Knowledge Distillation Model for Medical Image Classification

arXiv preprint arXiv:2403.11226

Shahabedin Nabavi

Kian Anvari Hamedani

Mohsen Ebrahimi Moghaddam

Ahmad Ali Abin

Alejandro F Frangi

2024/3/17

Mathematical preliminaries

Carlos Alberola-López

Alejandro F Frangi

2024/1/1

Accelerated simulation methodologies for computational vascular flow modelling

Michael MacRaild

Ali Sarrami-Foroushani

Toni Lassila

Alejandro F Frangi

2024/2/14

Simultaneous Super-Resolution and Denoising on MRI via Conditional Stochastic Normalizing Flow

Zhenhong Liu

Xingce Wang

Zhongke Wu

Yi-Cheng Zhu

Alejandro F Frangi

2023/12/5

A conditional flow variational autoencoder for controllable synthesis of virtual populations of anatomy

Haoran Dou

Nishant Ravikumar

Alejandro F Frangi

2023/10/1

See List of Professors in Alejandro F Frangi University(University of Leeds)

Co-Authors

H-index: 122
Max Viergever

Max Viergever

Universiteit Utrecht

H-index: 100
Wiro Niessen

Wiro Niessen

Erasmus Universiteit Rotterdam

H-index: 83
Steffen E Petersen

Steffen E Petersen

Queen Mary University of London

H-index: 66
Juan Cebral

Juan Cebral

George Mason University

H-index: 52
Julia A Schnabel

Julia A Schnabel

King's College

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