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José Adriano Azevedo da Silva Ribeiro Pinto (citation name: Adriano Pinto) completed the PhD Program in Computer Science of the Universities of Minho, Aveiro and Porto in 2020/07/27, having a Integrated Masters Degree in Biomedical Engineering in 2015/09 by Universidade do Minho (specialization in Medical Electronics). During his research activities he published 6 articles in journals. Has 1 book(s). According to Scopus, at the end of 2020, he had an h-index of 9 with more than 1000 citations. He was co-author in 7 scientific publications. Conducts research in the area(s) of Exact Sciences with emphasis on Computer. His main research area is Medical Imaging Analysis focusing on Machine Learning methods applied to neuroimaging acquisitions. Particularly, the main topic of his current research is the development of automatic machine learning methods to predict the stroke lesion 90-days after the onset acquisition. Adriano Pinto has also teaching experience at the Dept. Industrial Electronics, University of Minho, in the fields of Signal Processing and Electronics. Until present time, he advised 3 MSc. students (all of them finalized).
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Identification

Personal identification

Full name
José Adriano Azevedo da Silva Ribeiro Pinto

Citation names

  • Pinto, Adriano

Author identifiers

Ciência ID
F418-4F2D-D7DC
ORCID iD
0000-0001-9397-3722
Google Scholar ID
https://scholar.google.pt/citations?user=gokIeOIAAAAJ&hl=pt-PT

Addresses

  • Universidade do Minho, CMEMS, DEI, Campus de Azurém, 4800-058, Guimarães, Guimarães, Portugal (Professional)

Knowledge fields

  • Exact Sciences - Computer and Information Sciences - Information Science
  • Engineering and Technology

Languages

Language Speaking Reading Writing Listening Peer-review
English Advanced (C1) Advanced (C1) Intermediate (B1) Advanced (C1)
Education
Degree Classification
2015/09 - 2020/07/27
Concluded
 MAP-i (Doutoramento)
Universidade do Minho, Portugal

Universidade do Porto, Portugal

Universidade de Aveiro, Portugal
"Automatic prediction ischemic stroke from MRI images using Deep Learning." (THESIS/DISSERTATION)
 Unanimously Approved
2015/09
Concluded
 Mestrado Integrado em Engenharia Biomédica (Mestrado)
Universidade do Minho Escola de Engenharia, Portugal
"Segmentação do Tecido Tumoral Cerebral em Imagens de Ressonância Magnética" (THESIS/DISSERTATION)
 17
Affiliation

Teaching in Higher Education

Category
Host institution 		Employer
2019/09 - 2020/02 Invited Assistant (University Teacher) Universidade do Minho, Portugal
Universidade do Minho Escola de Engenharia, Portugal
2018/09 - 2019/02 Invited Assistant (University Teacher) Universidade do Minho, Portugal
Universidade do Minho Escola de Engenharia, Portugal
Outputs

Publications

Conference paper
  1. Amorim, Joana; Pinto, Adriano; Pereira, Sergio; Silva, Carlos A.. "Segmentation Squeeze-and-Excitation Blocks in Stroke Lesion Outcome Prediction". Paper presented in IEEE 6th Portuguese Meeting on Bioengineering (ENBENG), Lisbon, 2019.
    Published • 10.1109/enbeng.2019.8692549
  2. Pinto, Adriano. "Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction". Paper presented in Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, 2018.
    Published • https://doi.org/10.1007/978-3-030-00931-1_13
  3. Pereira, S.; Pinto, A.; Alves, V.; Silva, C.A.. "Deep convolutional neural networks for the segmentation of gliomas in multi-sequence MRI". 2015.
    10.1007/978-3-319-30858-6_12
  4. Pinto, A.; Pereira, S.; Correia, H.; Oliveira, J.; Rasteiro, D.M.L.D.; Silva, C.A.. "Brain Tumour Segmentation based on Extremely Randomized Forest with high-level features". 2015.
    10.1109/EMBC.2015.7319032
  5. Pinto, A.; Pereira, S.; Dinis, H.; Silva, C.A.; Rasteiro, D.M.L.D.. "Random decision forests for automatic brain tumor segmentation on multi-modal MRI images". 2015.
    10.1109/ENBENG.2015.7088842
Journal article
  1. Pinto, Adriano; Amorim, Joana; Hakim, Arsany; Alves, Victor; Reyes, Mauricio; Silva, Carlos A.. "Prediction of Stroke lesion at 90-day follow-up by fusing raw DSC-MRI with parametric maps using Deep Learning". IEEE Access (2021): 1-1. http://dx.doi.org/10.1109/access.2021.3058297.
    Published • 10.1109/access.2021.3058297
  2. Sergio Pereira; Adriano Pinto; Joana Amorim; Alexandrine Ribeiro; Victor Alves; Carlos A. Silva. "Adaptive Feature Recombination and Recalibration for Semantic Segmentation With Fully Convolutional Networks". IEEE Transactions on Medical Imaging 38 12 (2019): 2914-2925. https://doi.org/10.1109/TMI.2019.2918096.
    10.1109/TMI.2019.2918096
  3. Pinto, Adriano; Mckinley, Richard; Alves, Victor; Wiest, Roland; Silva, Carlos A.; Reyes, Mauricio. "Stroke Lesion Outcome Prediction Based on MRI Imaging Combined With Clinical Information". Frontiers in Neurology 9 (2018): http://dx.doi.org/10.3389/fneur.2018.01060.
    Published • 10.3389/fneur.2018.01060
  4. Adriano Pinto; Sérgio Pereira; Deolinda Rasteiro; Carlos A. Silva. "Hierarchical brain tumour segmentation using extremely randomized trees". Pattern Recognition 82 (2018): 105-117. https://doi.org/10.1016/j.patcog.2018.05.006.
    Published • 10.1016/j.patcog.2018.05.006
  5. Winzeck, Stefan; Hakim, Arsany; McKinley, Richard; Pinto, José A. A. D. S. R.; Alves, Victor; Silva, Carlos; Pisov, Maxim; et al. "ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI". Frontiers in Neurology 9 (2018): http://dx.doi.org/10.3389/fneur.2018.00679.
    10.3389/fneur.2018.00679
  6. Pereira, S.; Pinto, A.; Alves, V.; Silva, C.A.. "Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images". IEEE Transactions on Medical Imaging 35 5 (2016): 1240-1251. http://www.scopus.com/inward/record.url?eid=2-s2.0-84968610616&partnerID=MN8TOARS.
    10.1109/TMI.2016.2538465
  7. Pereira, S.; Pinto, A.; Oliveira, J.; Mendrik, A.M.; Correia, J.H.; Silva, C.A.. "Automatic brain tissue segmentation in MR images using Random Forests and Conditional Random Fields". Journal of Neuroscience Methods 270 (2016): 111-123. http://www.scopus.com/inward/record.url?eid=2-s2.0-84976433960&partnerID=MN8TOARS.
    10.1016/j.jneumeth.2016.06.017
Thesis / Dissertation
  1. Pinto, Adriano. "Segmentação do tecido tumoral cerebral em imagens de ressonância magnética". Master, Universidade do Minho Escola de Engenharia, 2015. http://hdl.handle.net/1822/39647.
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2018/09 Enhancing clinical MRI Perfusion maps with data-driven maps of complementary nature for lesion outcome prediction International Conference on Medical Image Computing and Computer-Assisted Intervention
(Granada, Spain)

Supervision

Thesis Title
Role 		Degree Subject (Type)
Institution / Organization
2021/09/01 - 2022/10/28 Monitoring and Prevention of Adversarial Attacks on Machine Learning Model
Co-supervisor
 Ciências de Engenharia Biomédica
Universidade do Minho, Portugal

Event organisation

Event name
Type of event (Role) 		Institution / Organization
2021/02 - Current Topic Editor of the special issue "Leveraging Machine and Deep Learning Technologies for Clinical Applications in Stroke Imaging" at Frontiers in Neurology (IF: 2.889) (2021/02)
Other (Co-organisor)
 Frontiers in Neurology, Switzerland

Event participation

Activity description
Type of event 		Event name
Institution / Organization
2019/03/27 - 2019/03/27 IEEE Student Branch Talk
Round table
 Talk About Artificial Intelligence
IEEE, United States
2016/06/20 - 2016/06/23 Summer School in Advanced Scientific Computing
Seminar
Universidade do Minho Escola de Engenharia, Portugal
2013/04/12 - 2013/04/12 Fair of professions and training offers show.
Exhibition
 Chosen spokesman to speak, and clarify doubts, with High-School students about the Integrated Masters in Biomedical Engineering.
Escola Secundária Carlos Amarante, Portugal
2013/03/13 - 2013/03/16 RoboParty - Universidadedo Minho
Other
Universidade do Minho, Portugal

Jury of academic degree

Topic
Role 		Candidate name (Type of degree)
Institution / Organization
2022/12/07 Automatic Driving: 2D Detection and Tracking using Artificial Intelligence Techniques
(Thesis) Main arguer
 José Miguel Fernandes Madeira Pinto (Master)
Universidade do Minho, Portugal
2022/01/18 Soluções Configuráveis para Inspeção Visual Automática
(Thesis) Main arguer
 Daniel Vilaça da Costa (Master)
Universidade do Minho, Portugal

Association member

Society Organization name Role
2020/01 - 2020/12 IEEE Computational Intelligence Society Member
2015 - 2016 Refood Braga 100% Volunteer

Course / Discipline taught

Academic session Degree Subject (Type) Institution / Organization
2019/09 - 2020/03 Electronics Mestrado Integrado em Engenharia Biomédica (Mestrado integrado) Universidade do Minho, Portugal
2019 - 2020 Processamento de Sinal Contínuo e Discreto Mestrado Integrado em Engenharia Biomédica (Mestrado integrado) Universidade do Minho, Portugal
2018/09 - 2019/03 Processamento de Sinal Contínuo e Discreto Mestrado Integrado em Engenharia Biomédica Universidade do Minho, Portugal
2018/09 - 2019/03 Processamento de Sinal Contínuo e Discreto Mestrado Integrado em Engenharia Física (Mestrado integrado) Universidade do Minho, Portugal

Evaluation committee

Activity description
Role 		Institution / Organization Funding entity
2018 - Current Peer-reviewer at international Journals: Neurocomputing, NeuroImage: Clinical, Frontiers in Neuroscience, Computers in Biology and Medicine, Sensors and iMIMIC Workshop.
Evaluator