Projects
Completed

ABIGAIL: AI-Boosted Imaging for Glioma Analysis, Identification, and Localization

The ABIGAIL project epitomizes a meticulous AI approach to enhance brain glioma diagnosis using advanced integration of MRI techniques and patient health records. The project has three primary objectives:

  • Develop a refined classification model for brain gliomas. This model combines MRI scans with patient health records using a dual-stream multimodal classification network, harnessing the potential of unlabeled data through weakly and semi-supervised learning methods.
  • Introduce an advanced assessment model to discern treatment response, focusing on differentiating between progression and pseudo progression, particularly in anaplastic astrocytoma and glioblastoma.
  • Provide precise segmentation of tumor and organs at risk. By amalgamating advanced neural networks with clinical data, ABIGAIL aims to set a innovative non-invasive approach for glioma diagnostics and analysis.

Funded by the European Union - NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I05-03-V02-00044.

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More projects of Peter Drotár

2024 – 2027

2D/3D Image Fusion for Image Guided Intervention
The main goal of the project is to propose a complete methodological approach for 2D/3D image fusion, based on 2D/3D registration. We assume two types of 2D data, fluoroscopy and USG data. The USG data represents a more challenging scenario due to their nature. As 3D data, the CT scans are to be used. Based on this we focus mainly on the hip anatomical area and thoracic area.
Slovak Research and Development Agency

2024 – 2026

Deep neural networks for medical image segmentation
The main objective of this project is to develop new methods for processing medical images while using the class-imbalanced nature of these data. We also aim to propose a new segmentation method for anatomical structures in the abdominal area, such as organs, tumors, and cysts. This task represents a significant challenge due to the complexity of the abdominal area and the diversity of anatomical structures that need to be precisely identified.
Scientific Grant Agency of the Ministry of Education, science, research and sport of the Slovak Republic and the Slovak Academy of Sciences

2024 – 2026

AInnotator: AI-powered Annotation in Medical Imaging
This project endeavors to develop Ainnotator, an innovative medical annotation tool set to improve medical imaging analysis.
European Union – NextGenerationEU