INESC TEC
INESC TEC
INESC TEC
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NanoStima-RL5

INESC TEC

About the 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 Cardoso

Status

Closed

Starting Date

January 1, 2015

Ending Date

January 30, 2019

Effective End Date

January 30, 2019

Global Budget

--

Funding

€317,832.00

Website

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Datasheet

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Associated Centres

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

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

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.

Artificial Intelligence and Decision Support

Telecommunications and Multimedia

The Centre for Telecommunications and Multimedia (CTM) welcomes close to 200 members, including at least 100 integrated researchers who carry out scientific work in the fields of communications, Artificial Intelligence, and computer science and engineering. The Centre’s activities cover several Research and Development (R&D) domains: Communications and Electronics Radio Frequency Technologies Optoelectronics Microelectronics Wireless Communication Networks Computer Perception Computer Vision applied to Medical Imaging Computer Vision applied to Digital Media Computer Audio applied to Music With multidisciplinary teams that include dozens of PhDs, CTM is strongly committed to both European and national research projects, as well as consultancy projects with industry.

Telecommunications and Multimedia