Completed

AInnotator: AI-powered Annotation in Medical Imaging

This project endeavors to develop Ainnotator, an innovative medical annotation tool set to improve medical imaging analysis. Aimed at overcoming the challenges of data scarcity and privacy concerns in healthcare, this tool integrates advanced learning paradigms—semi-supervised, weakly supervised, and federated learning—to optimize the use of both labeled and unlabeled data while maintaining strict data privacy. Ainnotator is designed to enhance operational efficiency in image analysis, foster collaboration among medical professionals, and ultimately improve patient care outcomes.

Funded by the European Union - NextGenerationEU through the Recovery and Resilience Plan for Slovakia under the project No. 09I05-03-V02-00017.

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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

Principal investigatorprof. Ing. Peter Drotár, PhD.

Active

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

Principal investigatorprof. Ing. Peter Drotár, PhD.

Active

2024 – 2026

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.

European Union – NextGenerationEU

Principal investigatorprof. Ing. Peter Drotár, PhD.

Completed