Saul Fuster Navarro

Forsker i informasjonsteknologi

Saul Fuster Navarro

Kontakt

E-post: saul.fusternavarro@uis.no

Rom: KE E-401

Organisasjonsenhet

Det teknisk-naturvitenskapelige fakultet

Institutt for data- og elektroteknologi

Kort om meg

Saul Fuster Navarro is currently employed as a post-doctoral researcher at the Department of Electrical Engineering and Computer Science (TN-IDE). Currently, he works under the NewbornTime project for newborn resuscitation video activity recognition in collaboration with Stavanger University Hospital and Laerdal Medical. He completed a Ph.D. in Science and Technology at UiS in 2024, on the topic of developing computer vision artificial intelligence algorithms for histopathological images of bladder cancer. The work carried out during the PhD period was funded under a Horizon 2020 Marie Curie grant. Also, he completed his B.Sc. and Master of Telecommunications Engineering from Universitat Politècnica de València, Spain, in 2017 and 2019 respectively.

Dette forsker jeg på

Under the NewbornTime project, he aims to develop a deep learning model for video activity recognition of resuscitation episodes of newborn. The main objective is to combine the model's predictions with the estimated time of birth to create a timeline that includes all activities from birth to the subsequent resuscitation.

Akademisk bakgrunn

His research interests are in artificial intelligence algorithms particularly with computer vision.

 

Publikasjoner

Vitenskapelige publikasjoner

Fuster Navarro, Saul; Kiraz, Umay; Eftestøl, Trygve Christian; Janssen, Emiel; Engan, Kjersti

(2024)

NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning.

Bioengineering.

ISSN 2306-5354.

Volum 11.

Hefte 9.

DOI: 10.3390/bioengineering11090909

Bø-Sande, Marie; Benjaminsen, Edvin; Kanwal, Neel; Fuster Navarro, Saul; Hardardottir, Helga; Lundal, Ingrid; Janssen, Emiel; Engan, Kjersti

(2024)

A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics.

Proceedings of Machine Learning Research (PMLR).

ISSN 2640-3498.

s.20-26.

Khoraminia, Farbod; Fuster Navarro, Saul; Kanwal, Neel; Olislagers, Mitchell; Engan, Kjersti; Leenders, Geet J.L.H. Van; Stubbs, Andrew P; Akram, Farhan; Zuiverloon, Tahlita C.M.

(2023)

Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review.

Cancers.

ISSN 2072-6694.

Volum 15.

Hefte 18.

DOI: 10.3390/cancers15184518

Andreassen, Christopher; Fuster Navarro, Saul; Hardardottir, Helga; Janssen, Emiel; Engan, Kjersti

(2023)

Deep Learning for Predicting Metastasis on Melanoma Wsis.

IEEE International Symposium on Biomedical Imaging.

ISSN 1945-7928.

DOI: 10.1109/ISBI53787.2023.10230474

Fuster Navarro, Saul; Khoraminia, Farbod; Eftestøl, Trygve Christian; Zuiverloon, Tahlita C M; Engan, Kjersti

(2023)

Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Images.

European Signal Processing Conference.

ISSN 2076-1465.

s.1045-1049.

DOI: 10.23919/EUSIPCO58844.2023.10290058

Fuster Navarro, Saul; Khoraminia, Farbod; Kiraz, Umay; Kanwal, Neel; Kvikstad, Vebjørn; Eftestøl, Trygve Christian; Zuiverloon, Tahlita C M; Janssen, Emiel; Engan, Kjersti

(2022)

Invasive cancerous area detection in non-muscle invasive bladder cancer whole slide images. I: 2022 IEEE 14th image video and multidimensional signal processing workshop (IVMSP) : 26-29 June 2022 : Nafplio, Greece.

IEEE conference proceedings.

ISBN 9781665478229.

DOI: 10.1109/IVMSP54334.2022.9816352

Kanwal, Neel; Fuster Navarro, Saul; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Chunming, Rong; Engan, Kjersti

(2022)

Quantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images. I: 2022 IEEE 14th image video and multidimensional signal processing workshop (IVMSP) : 26-29 June 2022 : Nafplio, Greece.

IEEE conference proceedings.

ISBN 9781665478229.

DOI: 10.1109/IVMSP54334.2022.9816283

Fuster Navarro, Saul; Eftestøl, Trygve Christian; Engan, Kjersti

(2022)

Nested multiple instance learning with attention mechanisms. I: Proceedings 21st IEEE international conference on machine learning and applications : ICMLA 2022.

IEEE conference proceedings.

ISBN 978-1-6654-6283-9.

s.220-225.

DOI: 10.1109/ICMLA55696.2022.00038

Formidling

Fuster Navarro, Saul; Eftestøl, Trygve Christian; Engan, Kjersti; Kiraz, Umay; Janssen, Emiel; Kvikstad, Vebjørn

(2022)

Towards Automatic Staging of Non-Muscle Invasive Bladder Cancer.

NORA 2022;

2022-06-09 - 2022-06-10.

Fuster Navarro, Saul; Eftestøl, Trygve Christian; Engan, Kjersti; Kiraz, Umay; Janssen, Emiel; Kvikstad, Vebjørn

(2022)

Towards Automatic Staging of NonMuscle Invasive Bladder Cancer.

hAIST 22;

2022-06-13 - 2022-06-14.

Fuster Navarro, Saul; Eftestøl, Trygve Christian; Engan, Kjersti; Kiraz, Umay; Kvikstad, Vebjørn; Janssen, Emiel

(2022)

Invasive Cancerous Area Detection in Non-Muscle Invasive Bladder Cancer Whole Slide Images.

IVMSP 2022;

2022-06-26 - 2022-06-29.

Fuster Navarro, Saul; Eftestøl, Trygve Christian; Engan, Kjersti

(2022)

Nested Multiple Instance Learning with Attention Mechanisms.

ICMLA 2022;

2022-12-12 - 2022-12-14.

Engan, Kjersti; Wetteland, Rune; Fuster Navarro, Saul; Kanwal, Neel

(2022)

Examples of artificial intelligence in computational pathology .

hAIst Conference – Health-related Artificial Intelligence in Stavanger;

2022-06-13 - 2022-06-14.

Fuster Navarro, Saul; Engan, Kjersti; Eftestøl, Trygve Christian

(2021)

A Nested Multiple Instance Learning Framework.

NOBIM 2021;

2021-09-13 - 2021-09-14.