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Fernando Navarro

About Fernando Navarro

Fernando Navarro, With an exceptional h-index of 14 and a recent h-index of 14 (since 2020), a distinguished researcher at Technische Universität München, specializes in the field of Machine Learning, Deep Learning, Computer Vision, Medical Image Computing.

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

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

PO-1634 Validation of a U-Net-based algorithm for MRI-guided extremity soft tissue sarcoma GTV segmentation

A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images

The liver tumor segmentation benchmark (lits)

Focused decoding enables 3D anatomical detection by transformers

Self-supervised pretext tasks in model robustness & generalizability: A revisit from medical imaging perspective

A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning

SwinFPN: Leveraging Vision Transformers for 3D Organs-At-Risk Detection

Fernando Navarro Information

University

Position

___

Citations(all)

1520

Citations(since 2020)

1503

Cited By

122

hIndex(all)

14

hIndex(since 2020)

14

i10Index(all)

15

i10Index(since 2020)

15

Email

University Profile Page

Google Scholar

Fernando Navarro Skills & Research Interests

Machine Learning

Deep Learning

Computer Vision

Medical Image Computing

Top articles of Fernando Navarro

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

arXiv preprint arXiv:2312.17670

2023/12/29

Kaiyuan Yang
Kaiyuan Yang

H-Index: 4

Rami Al-Maskari
Rami Al-Maskari

H-Index: 2

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Florian Kofler
Florian Kofler

H-Index: 3

Fernando Navarro
Fernando Navarro

H-Index: 5

Ivan Ezhov
Ivan Ezhov

H-Index: 6

Daniel Rueckert
Daniel Rueckert

H-Index: 85

Jeroen Bisschop
Jeroen Bisschop

H-Index: 5

Bene Wiestler
Bene Wiestler

H-Index: 36

Adrian Galdran
Adrian Galdran

H-Index: 17

Francesco Galati
Francesco Galati

H-Index: 21

Haoran Zhao
Haoran Zhao

H-Index: 2

Zehan Zhang
Zehan Zhang

H-Index: 5

Hyunjin Park
Hyunjin Park

H-Index: 23

Wei Liu
Wei Liu

H-Index: 16

Ting Ma
Ting Ma

H-Index: 4

Joaquim Salvi
Joaquim Salvi

H-Index: 25

Xavier Llado
Xavier Llado

H-Index: 31

Arnau Oliver
Arnau Oliver

H-Index: 30

Yue Cui
Yue Cui

H-Index: 2

Maysam Orouskhani
Maysam Orouskhani

H-Index: 5

Mahmud Mossa-Basha
Mahmud Mossa-Basha

H-Index: 25

Chengcheng Zhu
Chengcheng Zhu

H-Index: 15

Yuki Sato
Yuki Sato

H-Index: 3

Susanne Wegener
Susanne Wegener

H-Index: 16

PO-1634 Validation of a U-Net-based algorithm for MRI-guided extremity soft tissue sarcoma GTV segmentation

Radiotherapy and Oncology

2023/5/1

A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images

Frontiers in neurology

2023/2/21

Giles Tetteh
Giles Tetteh

H-Index: 10

Fernando Navarro
Fernando Navarro

H-Index: 5

Bjoern H Menze
Bjoern H Menze

H-Index: 39

The liver tumor segmentation benchmark (lits)

Medical Image Analysis

2023/2/1

Eugene Vorontsov
Eugene Vorontsov

H-Index: 14

Avi Ben-Cohen
Avi Ben-Cohen

H-Index: 11

Georgios Kaissis
Georgios Kaissis

H-Index: 10

Adi Szeskin
Adi Szeskin

H-Index: 4

Colin Jacobs
Colin Jacobs

H-Index: 6

Felix Hofmann
Felix Hofmann

H-Index: 20

Ivan Ezhov
Ivan Ezhov

H-Index: 6

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Fernando Navarro
Fernando Navarro

H-Index: 5

Florian Kofler
Florian Kofler

H-Index: 3

Xiaobin Hu
Xiaobin Hu

H-Index: 8

Jan Kirschke
Jan Kirschke

H-Index: 32

Florian Ettlinger
Florian Ettlinger

H-Index: 6

Michela Antonelli
Michela Antonelli

H-Index: 19

Lei Bi
Lei Bi

H-Index: 19

Hao Chen
Hao Chen

H-Index: 7

Bogdan Georgescu
Bogdan Georgescu

H-Index: 3

Xavier Giró-I-Nieto
Xavier Giró-I-Nieto

H-Index: 23

Xu Han
Xu Han

H-Index: 12

Christian Igel
Christian Igel

H-Index: 30

Jae-Hun Kim
Jae-Hun Kim

H-Index: 31

Sungwoong Kim
Sungwoong Kim

H-Index: 6

Avinash Kori
Avinash Kori

H-Index: 8

Ganapathy Krishnamurthi
Ganapathy Krishnamurthi

H-Index: 17

Fan Li
Fan Li

H-Index: 9

Xiaomeng Li
Xiaomeng Li

H-Index: 7

John Lowengrub
John Lowengrub

H-Index: 45

Jun Ma
Jun Ma

H-Index: 25

Mathias Perslev
Mathias Perslev

H-Index: 4

Jens Petersen
Jens Petersen

H-Index: 12

Karsten Roth
Karsten Roth

H-Index: 7

Zengming Shen
Zengming Shen

H-Index: 3

Jordi Torres
Jordi Torres

H-Index: 33

Christian Wachinger
Christian Wachinger

H-Index: 23

Yading Yuan
Yading Yuan

H-Index: 11

Liping Zhang
Liping Zhang

H-Index: 10

Jorge Cardoso
Jorge Cardoso

H-Index: 26

Rickmer Braren
Rickmer Braren

H-Index: 24

Samuel Kadoury
Samuel Kadoury

H-Index: 28

Bram Van Ginneken
Bram Van Ginneken

H-Index: 71

Hayit Greenspan
Hayit Greenspan

H-Index: 39

Leo Joskowicz
Leo Joskowicz

H-Index: 26

Focused decoding enables 3D anatomical detection by transformers

arXiv preprint arXiv:2207.10774

2022/7/21

Fernando Navarro
Fernando Navarro

H-Index: 5

Self-supervised pretext tasks in model robustness & generalizability: A revisit from medical imaging perspective

2022/7/11

Fernando Navarro
Fernando Navarro

H-Index: 5

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Bjoern H Menze
Bjoern H Menze

H-Index: 39

A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning

2022/7/11

Fernando Navarro
Fernando Navarro

H-Index: 5

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Ivan Ezhov
Ivan Ezhov

H-Index: 6

Bjoern H Menze
Bjoern H Menze

H-Index: 39

SwinFPN: Leveraging Vision Transformers for 3D Organs-At-Risk Detection

2022/4/25

Fernando Navarro
Fernando Navarro

H-Index: 5

Automated detection of the contrast phase in MDCT by an artificial neural network improves the accuracy of opportunistic bone mineral density measurements

European Radiology

2022/3/1

Fernando Navarro
Fernando Navarro

H-Index: 5

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Rickmer Braren
Rickmer Braren

H-Index: 24

Tumor sink effect in 68Ga-PSMA-11 PET: myth or reality?

Journal of Nuclear Medicine

2022/2/1

Hui Wang
Hui Wang

H-Index: 2

Andrew Robertson
Andrew Robertson

H-Index: 8

Fernando Navarro
Fernando Navarro

H-Index: 5

David Elashoff
David Elashoff

H-Index: 51

Development and Benchmarking of a Deep Learning/UNet-based Algorithm for automatic MRI-assisted GTV Segmentation of Soft-tissue Sarcomas of the Extremities

2022

Robust, primitive, and unsupervised quality estimation for segmentation ensembles

Frontiers in Neuroscience

2021/12/30

Florian Kofler
Florian Kofler

H-Index: 3

Ivan Ezhov
Ivan Ezhov

H-Index: 6

Lucas Fidon
Lucas Fidon

H-Index: 7

Sarthak Pati
Sarthak Pati

H-Index: 9

Fernando Navarro
Fernando Navarro

H-Index: 5

Jan Kirschke
Jan Kirschke

H-Index: 32

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Geometry-aware neural solver for fast Bayesian calibration of brain tumor models

IEEE Transactions on Medical Imaging

2021/12/20

Ivan Ezhov
Ivan Ezhov

H-Index: 6

Jana Lipkova
Jana Lipkova

H-Index: 8

Florian Kofler
Florian Kofler

H-Index: 3

Chantal Pellegrini
Chantal Pellegrini

H-Index: 1

Marcel Kollovieh
Marcel Kollovieh

H-Index: 1

Fernando Navarro
Fernando Navarro

H-Index: 5

Hongwei Li
Hongwei Li

H-Index: 19

A deep learning approach to predicting collateral flow in stroke patients using radiomic features from perfusion images

arXiv preprint arXiv:2110.12508

2021/10/24

Giles Tetteh
Giles Tetteh

H-Index: 10

Fernando Navarro
Fernando Navarro

H-Index: 5

Jan Kirschke
Jan Kirschke

H-Index: 32

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Development and external validation of deep-learning-based tumor grading models in soft-tissue sarcoma patients using MR imaging

Cancers

2021/6/8

Fernando Navarro
Fernando Navarro

H-Index: 5

Carolin Knebel
Carolin Knebel

H-Index: 9

Matthew B Spraker
Matthew B Spraker

H-Index: 13

Philippe Lambin
Philippe Lambin

H-Index: 68

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Evaluating the robustness of self-supervised learning in medical imaging

arXiv preprint arXiv:2105.06986

2021/5/14

Fernando Navarro
Fernando Navarro

H-Index: 5

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Differenzierung von atypischen lipomatösen Tumoren und Lipomen durch Deep Learning Analysen

RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren

2021/4

Deep learning-enabled multi-organ segmentation in whole-body mouse scans

Nature communications

2020/11/6

Javier Coronel
Javier Coronel

H-Index: 2

Zhouyi Rong
Zhouyi Rong

H-Index: 5

Fernando Navarro
Fernando Navarro

H-Index: 5

Hongwei Li
Hongwei Li

H-Index: 19

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Deep reinforcement learning for organ localization in CT

2020/9/21

Fernando Navarro
Fernando Navarro

H-Index: 5

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Bjoern H Menze
Bjoern H Menze

H-Index: 39

Grading loss: a fracture grade-based metric loss for vertebral fracture detection

2020

Anjany Sekuboyina
Anjany Sekuboyina

H-Index: 9

Fernando Navarro
Fernando Navarro

H-Index: 5

Bjoern H Menze
Bjoern H Menze

H-Index: 39

See List of Professors in Fernando Navarro University(Technische Universität München)

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