Mitko Veta

Orcid: 0000-0003-1711-3098

According to our database1, Mitko Veta authored at least 56 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset.
IEEE J. Biomed. Health Informatics, March, 2024

WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide images.
CoRR, 2024

Multiple Instance Learning with random sampling for Whole Slide Image Classification.
CoRR, 2024

Tissue Cross-Section and Pen Marking Segmentation in Whole Slide Images.
CoRR, 2024

Abstract: Comprehensive Multi-domain Dataset for Mitotic Figure Detection.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound.
IEEE J. Biomed. Health Informatics, September, 2023

Mitosis domain generalization in histopathology images - The MIDOG challenge.
Medical Image Anal., 2023

Domain generalization across tumor types, laboratories, and species - insights from the 2022 edition of the Mitosis Domain Generalization Challenge.
CoRR, 2023

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge.
CoRR, 2023

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset.
CoRR, 2023

Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Physics-informed neural networks for myocardial perfusion MRI quantification.
Medical Image Anal., 2022

Mitosis domain generalization in histopathology images - The MIDOG challenge.
CoRR, 2022

Optimized automated cardiac MR scar quantification with GAN-based data augmentation.
Comput. Methods Programs Biomed., 2022

2021
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.
IEEE Trans. Medical Imaging, 2021

Editorial Computational Pathology.
IEEE J. Biomed. Health Informatics, 2021

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI.
IEEE Trans. Biomed. Eng., 2021

Intensity Augmentation to Improve Generalizability of Breast Segmentation Across Different MRI Scan Protocols.
IEEE Trans. Biomed. Eng., 2021

Roto-translation equivariant convolutional networks: Application to histopathology image analysis.
Medical Image Anal., 2021

Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.
Medical Image Anal., 2021

Quantifying the Scanner-Induced Domain Gap in Mitosis Detection.
CoRR, 2021

Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty.
CoRR, 2021

Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans.
Proceedings of the Ophthalmic Medical Image Analysis - 8th International Workshop, 2021

2020
Progressively Trained Convolutional Neural Networks for Deformable Image Registration.
IEEE Trans. Medical Imaging, 2020

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images.
CoRR, 2020

Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology.
CoRR, 2020

Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks.
CoRR, 2020

A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging.
CoRR, 2020

Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

Are Pathologist-Defined Labels Reproducible? Comparison of the TUPAC16 Mitotic Figure Dataset with an Alternative Set of Labels.
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Direct classification of type 2 diabetes from retinal fundus images in a population-based sample from the Maastricht study.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Segmentation and Classification of Melanoma and Nevus in Whole Slide Images.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis.
Proceedings of the Automated Reasoning for Systems Biology and Medicine, 2019

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.
Medical Image Anal., 2019

Corrigendum to "Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge" [Medical Image Analysis, 54 (2019) 111-121].
Medical Image Anal., 2019

Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk.
CoRR, 2019

Intensity augmentation for domain transfer of whole breast segmentation in MRI.
CoRR, 2019

Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI.
CoRR, 2019

Automatic cardiac landmark localization by a recurrent neural network.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Approximation of a pipeline of unsupervised retina image analysis methods with a CNN.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Detection of acini in histopathology slides: towards automated prediction of breast cancer risk.
Proceedings of the Medical Imaging 2019: Digital Pathology, 2019

Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

2018
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge.
CoRR, 2018

Deformable image registration using convolutional neural networks.
Proceedings of the Medical Imaging 2018: Image Processing, 2018

Convolutional Neural Networks for Segmentation of the Left Atrium from Gadolinium-Enhancement MRI Images.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Inferring a third spatial dimension from 2D histological images.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Adversarial Training and Dilated Convolutions for Brain MRI Segmentation.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Exploring the Similarity of Medical Imaging Classification Problems.
Proceedings of the Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2017

2016
Cutting Out the Middleman: Measuring Nuclear Area in Histopathology Slides Without Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015
Assessment of algorithms for mitosis detection in breast cancer histopathology images.
Medical Image Anal., 2015

2014
Corrections to "Breast Cancer Histopathology Image Analysis: A Review".
IEEE Trans. Biomed. Eng., 2014

Breast Cancer Histopathology Image Analysis: A Review.
IEEE Trans. Biomed. Eng., 2014

2013
Detecting mitotic figures in breast cancer histopathology images.
Proceedings of the Medical Imaging 2013: Digital Pathology, 2013

2011
Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011


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