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INESC TEC
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NanoStima-RL5

INESC TEC

About Project

NanoSTIMA - Advanced Methodologies for Computer-Aided Detection and Diagnosis

The goal of CAD-RL5 is to develop advanced capabilities for computer-aided detection and diagnosis (CAD). This requires research on innovative methodologies for CAD development, that will make it possible to go from ad hoc engineering approaches, driven by direct expert knowledge, to more automated approaches, driven by the intrinsic structure of data, knowledge discovery and expert supervision. Problems tackled will be generic in the sense that appropriate outcomes can be applied universally to medical imaging practices. The developed method will enable lab demonstrations of several clinical problems where the research team has relevant experience (e.g. radiology, ophthalmology and ultrasound imaging).

Project Information Sheet (PT)

Acronym

NanoStima-RL5

Responsible

Jaime dos Santos Cardoso

Status

Closed

Start

January 1, 2015

End

January 30, 2019

Effective End

January 30, 2019

Global Budget

--

Financing

€317,832.00

Members

Team Leaders
Jaime dos Santos Cardoso

Jaime S. Cardoso holds a Licenciatura (5-year degree) in Electrical and Computer Engineering in 1999, an MSc in Mathematical Engineering in 2005 and a Ph.D. in Computer Vision in 2006, all from the University of Porto.


Cardoso is an Associate Professor with Habilitation at the Faculty of Engineering of the University of Porto (FEUP), where he has been teaching Machine Learning and Computer Vision in Doctoral Programs and multiple courses for the graduate studies. Cardoso is currently a Senior Researcher of the ‘Information Processing and Pattern Recognition’ Area in the Telecommunications and Multimedia Unit of INESC TEC. He is also Senior Member of IEEE and co-founder of ClusterMedia Labs, an IT company developing automatic solutions for semantic audio-visual analysis.


His research can be summed up in three major topics: computer vision, machine learning and decision support systems. Cardoso has co-authored 150+ papers, 50+ of which in international journals. Cardoso has been the recipient of numerous awards, including the Honorable Mention in the Exame Informática Award 2011, in software category, for project “Semantic PACS” and the First Place in the ICDAR 2013 Music Scores Competition: Staff Removal (task: staff removal with local noise), August 2013. The research results have been recognized both by the peers, with 6500+ citations to his publications and the advertisement in the mainstream media several times.

Aurélio Joaquim de Castro Campilho

Aurélio Campilho is Emeritus Professor of the University of Porto, Jubilee Full Professor in the Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, Portugal. He is a Fellow from EAMBES (European Alliance of Medical and Biological Engineering and Science). He is a Senior Member of the IEEE – The Institute of Electrical and Electronics Engineers. He is coordinator of the Center for Biomedical Engineering Research (C-BER) and develops research at the Biomedical Imaging Lab from C-BER from INESC TEC – Institute for Systems and Computer Engineering, Technology and Science. His current research interests include the areas of biomedical engineering, medical image analysis, image processing and computer vision, particularly in Computer-aided Diagnosis applied in several imaging modalities, including ophthalmic images, carotid ultrasound imaging and computed tomography of the lung.

He is the author of one book (with two editions), co-edited 20 books and published more than 250 articles in international journals and conferences. Organized several special issues of magazines and conferences. He was Associate Editor of the journals IEEE Transactions on Biomedical Engineering and the Machine Vision Applications Journal. From 2004 to 2020, he was General Chair of the International Conferences on Image Analysis and Recognition (ICIAR) conference series.


 

 

Carlos Manuel Abreu Gomes Ferreira

Associated Centres

Biomedical Engineering Research

The impact that science and innovation can have on the prevention, early detection, and support for the diagnosis of various types of diseases is fully explored at our Centre for Biomedical Engineering Research (C-BER). Guided by an interdisciplinary approach that prioritises technology transfer with economic impact—through the creation of new systems, tools, and methods related to disease diagnosis and monitoring, ageing, human rehabilitation, physiotherapy, and functional assessment—our researchers are dedicated to developing advanced technologies positioned at the intersection of engineering, medicine and health, and general well-being. Promoting strategic partnerships with clinical partners, research institutes, and encouraging international cooperation is one of the centre’s key priorities. Its research is structured across three distinct areas: Biomedical Imaging, Bioinstrumentation, and Neuroengineering.

Biomedical Engineering Research

Advanced Computing Systems

The Centre for Advanced Computing Systems (CRACS) strives for scientific excellence in the areas of programming languages, parallel and distributed computing, information mining, security and privacy, focusing on developing scalable software systems for multidisciplinary applications in Engineering, Life Sciences, Social Networks, the Internet of Things, and more. We explore deep theoretical and practical knowledge related to the design and development of programming languages and middleware for advanced computing systems - including parallel, distributed, high-performance, cloud, wireless, and IoT systems -, while mastering the concepts and methodologies that underpin trust, privacy, and security in computing systems. Our research environment brings together talented junior and senior researchers, most of whom are university lecturers. Together, they form the critical mass and scientific expertise required to fulfil our mission.

Advanced Computing Systems