Onderzoeksoutput per jaar
Persoonlijk profiel
Research profile
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.
Academic background
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.
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- 2 Vergelijkbare profielen
Breast Neoplasms
Medicijnen en Levenswetenschappen
Image analysis
Engineering en materiaalwetenschappen
Pathology
Engineering en materiaalwetenschappen
Tissue
Engineering en materiaalwetenschappen
Segmentation
Rekenkunde
Neural networks
Engineering en materiaalwetenschappen
Male Breast Neoplasms
Medicijnen en Levenswetenschappen
Color
Engineering en materiaalwetenschappen
Netwerk
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Onderzoeksoutput 2011 2019
Approximation of a pipeline of unsupervised retina image analysis methods with a CNN
Heslinga, F., Pluim, J., Dasht Bozorg, B., Berendschot, T., Houben, A. J. H. M., Henry, R. M. A. & Veta, M., 1 mrt 2019, Image Processing: SPIE Medical Imaging, 2019, San Diego, California, United States. Angelini, E. D. & Landman, B. A. (redactie). Bellingham: SPIE, 7 blz. 109491N. (Proceedings of SPIE; vol. 10949)Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
Biomarkers
Image analysis
Pipelines
Neural networks
Medical problems
Automated clear cell renal carcinoma grade classification with prognostic significance
Tian, K., Rubadue, C. A., Lin, D. I., Veta, M., Pyle, M. E., Irshad, H. & Heng, Y. J., 1 jan 2019, In : PLoS ONE. 14, 10, 16 blz., e0222641Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › Academic › peer review
Open Access
Bestand
kidney cells
Renal Cell Carcinoma
carcinoma
Atlases
Hazards
Automatic cardiac landmark localization by a recurrent neural network
van Zon, M., Veta, M. & Li, S., 1 jan 2019, Medical Imaging 2019: Image Processing. Landman, B. A. & Angelini, E. D. (redactie). Bellingham: SPIE, 13 blz. 1094916. (Proceedings of SPIE; vol. 10949)Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
landmarks
Recurrent neural networks
Mitral Valve
Magnetic Resonance Spectroscopy
Magnetic resonance
Convolutional neural networks for segmentation of the left atrium from gadolinium-enhancement MRI images
de Vente, C., Veta, M., Razeghi, O., Niederer, S., Pluim, J., Rhode, K. & Karim, R., 14 feb 2019, Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges - 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers. Li, S., McLeod, K., Young, A., Rhode, K., Pop, M., Zhao, J., Mansi, T. & Sermesant, M. (redactie). Cham: Springer, blz. 348-356 9 blz. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11395 LNCS)Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
Gadolinium
Magnetic resonance
Convolution
Magnetic resonance imaging
Segmentation
Deep learning networks to segment and detect breast terminal duct lobular units, acini, and adipose tissue: a step toward the automated analysis of lobular involution as a marker for breast cancer risk
Onken, A., Wetstein, S., Pyle, M., Pluim, J., Schnitt, S., Baker, G., Collins, L., Tamimi, R., Veta, M. & Heng, Y., 2019, (Geaccepteerd/In druk) United States and Canadian Academy of Pathology (USCAP).Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic
Adipose Tissue
Breast
Learning
Breast Neoplasms
Physiological Phenomena
Cursussen
Scriptie
Canonical correlation analysis on microbial and metabolite data of individuals with metabolic syndrome
Auteur: van der Stam, J., 19 jan 2019Begeleider: Hilbers, P. (Afstudeerdocent 1), van Riel, N. (Afstudeerdocent 2), Veta, M. (Afstudeerdocent 2), Levin, E. (Externe persoon) (Externe coach) & Nieuwdorp, M. (Externe persoon) (Externe coach)
Scriptie/masterproef: Master
Causal candidate genes identification for familial hypercholesterolemia family based on whole-genome sequencing
Auteur: Wang, Q., 31 aug 2017Begeleider: Hilbers, P. (Afstudeerdocent 1), van Riel, N. (Afstudeerdocent 2), Hovingh, K. (Externe persoon) (Externe coach), Bosnacki, D. (Afstudeerdocent 2) & Veta, M. (Afstudeerdocent 2)
Scriptie/masterproef: Master
Content based CT retrieval for pulmonary nodules: deep metric learning based feature extraction
Auteur: Aerts, T., 28 feb 2019Begeleider: Menkovski, V. (Afstudeerdocent 1), Holenderski, M. (Afstudeerdocent 2) & Veta, M. (Afstudeerdocent 2)
Scriptie/masterproef: Master
Bestand
CycleGAN for coronay vessel segmentation
Auteur: van den Bosch, P., 29 aug 2019Begeleider: Pluim, J. (Afstudeerdocent 1), Bovendeerd, P. (Afstudeerdocent 2), Veta, M. (Afstudeerdocent 2) & Oliván-Bescós, J. (Externe persoon) (Externe coach)
Scriptie/masterproef: Master
Deep learning approaches for prostate cancer detection and grading in Bi-parametric MRI
Auteur: de Vente, C., 29 aug 2019Begeleider: Veta, M. (Afstudeerdocent 1), Vos, P. (Externe persoon) (Externe coach), van Riel, N. (Afstudeerdocent 2) & Pluim, J. (Afstudeerdocent 2)
Scriptie/masterproef: Master