DL-I-PBraTSC | Deep Learning Based Interpretable Pediatric Brain Tumors Segmentation and Classification

Summary
The DL-I-PBraTSC project aims to address the significant impact of pediatric brain tumors (PBTs) as the leading cause of cancer death in children and adolescents. Artificial Intelligence (AI) technologies are increasingly being explored to assist doctors in detecting and diagnosing through clinical decision support systems (CDSS). However, They face the challenges in successfully segmenting PBTs due to the scarcity of available medical image datasets. Additionally, the lack of transparency in black-box AI models has raised concerns among doctors, hindering the adoption of AI in CDSS. To tackle these challenges, the project will develop a state-of-the-art interpretable AI-based framework to classify PBTs including tumor segmentation. DL-I-PBraTSC will identify the location of PBTs, classify of PBT types, and enable quantitative analysis of sub-region of PBT parameters helping clinicians in diagnosis, treatment planning, monitoring disease progression, and predicting patient outcomes. The project will start with collecting and preparing sufficiently large, balanced PBT medical images from secondment hospital with the assistance of medical experts. An online test platform will be implemented for clinicians to use the model, gathering feedback for further validation and improvements. The non-academic placement will provide real-world clinical validation of the model's efficacy. The project findings will be shared in conferences or journals targeting both neuroscience and informatics. DL-I-PBraTSC can help healthcare providers make more informed decisions about diagnosis and treatment planning of PBTs and contribute to early detection and intervention. These can lead to better patient outcomes, improved overall healthcare delivery and public health outcomes, and reduced healthcare costs, aligning with the EU's objectives of providing ensuring the safety and well-being of its citizens and one of the Irish national research priorities areas, Health and Wellbeing.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101152004
Start date: 01-09-2024
End date: 28-02-2027
Total budget - Public funding: - 269 418,00 Euro
Cordis data

Original description

The DL-I-PBraTSC project aims to address the significant impact of pediatric brain tumors (PBTs) as the leading cause of cancer death in children and adolescents. Artificial Intelligence (AI) technologies are increasingly being explored to assist doctors in detecting and diagnosing through clinical decision support systems (CDSS). However, They face the challenges in successfully segmenting PBTs due to the scarcity of available medical image datasets. Additionally, the lack of transparency in black-box AI models has raised concerns among doctors, hindering the adoption of AI in CDSS. To tackle these challenges, the project will develop a state-of-the-art interpretable AI-based framework to classify PBTs including tumor segmentation. DL-I-PBraTSC will identify the location of PBTs, classify of PBT types, and enable quantitative analysis of sub-region of PBT parameters helping clinicians in diagnosis, treatment planning, monitoring disease progression, and predicting patient outcomes. The project will start with collecting and preparing sufficiently large, balanced PBT medical images from secondment hospital with the assistance of medical experts. An online test platform will be implemented for clinicians to use the model, gathering feedback for further validation and improvements. The non-academic placement will provide real-world clinical validation of the model's efficacy. The project findings will be shared in conferences or journals targeting both neuroscience and informatics. DL-I-PBraTSC can help healthcare providers make more informed decisions about diagnosis and treatment planning of PBTs and contribute to early detection and intervention. These can lead to better patient outcomes, improved overall healthcare delivery and public health outcomes, and reduced healthcare costs, aligning with the EU's objectives of providing ensuring the safety and well-being of its citizens and one of the Irish national research priorities areas, Health and Wellbeing.

Status

SIGNED

Call topic

HORIZON-MSCA-2023-PF-01-01

Update Date

16-11-2024
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Horizon Europe
HORIZON.1 Excellent Science
HORIZON.1.2 Marie Skłodowska-Curie Actions (MSCA)
HORIZON.1.2.0 Cross-cutting call topics
HORIZON-MSCA-2023-PF-01
HORIZON-MSCA-2023-PF-01-01 MSCA Postdoctoral Fellowships 2023