Mitko Veta is an assistant professor at the TU/e research group Medical Image Analysis, department of Biomedical Engineering. His research concerns the design, implementation and evaluation of image analysis methods for histopathology images and digital slides. Currently his focus is on the development and application of deep learning methods for medical image analysis. The research aims to develop automatic quantitative histopathology image analysis algorithms that will increase the reproducibility and accuracy of pathology reporting and reduce the workload of pathologists. This will lead to better treatment planning for the patients and reduction of healthcare costs.
MitkoVeta studied Electrical Engineering at the Ss. Cyril and Methodius University in Skopje (Macedonia) where he in 2009 received his Master's degree on Digital Signal Processing with a thesis on digital video classification. In 2010, he moved to the University Medical Center Utrecht (The Netherlands) to perform PhD research on the topic of automatic analysis of histopathology images. In 2014, he obtained his doctorate and started as a postdoctoral researcher at Eindhoven University of Technology (TU/e, the Netherlands). In 2016, he was appointed assistant professor with the TU/e research group Medical Image Analysis of the department of Biomedical Engineering.
Predicting breast tumor proliferation from whole-slide imagesMedical Image Analysis (2019)
Roto-translation covariant convolutional networks for medical image analysisarXiv (2018)
Deformable image registration using convolutional neural networks2018 SPIE Medical Imaging: Image Processing (2018)
Deformable image registration using convolutional neural networksSPIE Medical Imaging: Image Processing (2018)
Inferring a third spatial dimension from 2D histological images15th IEEE International Symposium on Biomedical Imaging (ISBI 2018) (2018)
- Team challenge in medical imaging
- Project Imaging - BIA
- Medical image analysis
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