Maria Vakalopoulou

Orcid: 0000-0002-3059-5741

According to our database1, Maria Vakalopoulou authored at least 76 papers between 2014 and 2024.

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Bibliography

2024
GHOST: Graph-based higher-order similarity transformation for classification.
Pattern Recognit., 2024

ADAPT: Multimodal Learning for Detecting Physiological Changes under Missing Modalities.
CoRR, 2024

ViG-Bias: Visually Grounded Bias Discovery and Mitigation.
CoRR, 2024

You Don't Need Data-Augmentation in Self-Supervised Learning.
CoRR, 2024

Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning.
CoRR, 2024

Diffusion Models for Nuclei Segmentation in Low Data Regimes.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023

Data-Centric Machine Learning for Geospatial Remote Sensing Data.
CoRR, 2023

On the detection of Out-Of-Distribution samples in Multiple Instance Learning.
CoRR, 2023

MEDIMP: Medical Images and Prompts for renal transplant representation learning.
CoRR, 2023

Improving Domain-Invariance in Self-Supervised Learning via Batch Styles Standardization.
CoRR, 2023

Towards better certified segmentation via diffusion models.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

MEDIMP: 3D Medical Images and clinical Prompts for renal transplant representation learning.
Proceedings of the Medical Imaging with Deep Learning, 2023

SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Certification of Deep Learning Models for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Structured State Space Models for Multiple Instance Learning in Digital Pathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology.
Proceedings of the Information Processing in Medical Imaging, 2023

Differentiable Gamma Index-Based Loss Functions: Accelerating Monte-Carlo Radiotherapy Dose Simulation.
Proceedings of the Information Processing in Medical Imaging, 2023

Have Foundational Models Seen Satellite Images?
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Spatio-Temporal Analysis of Patient-Derived Organoid Videos Using Deep Learning for the Prediction of Drug Efficacy.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
COMBING: Clustering in Oncology for Mathematical and Biological Identification of Novel Gene Signatures.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Artifact Removal in Histopathology Images.
CoRR, 2022

Hyper-AdaC: Adaptive clustering-based hypergraph representation of whole slide images for survival analysis.
Proceedings of the Machine Learning for Health, 2022

Gigapixel Whole-Slide Images Classification Using Locally Supervised Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Test-Time Image-to-Image Translation Ensembling Improves Out-of-Distribution Generalization in Histopathology.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Contrastive Masked Transformers for Forecasting Renal Transplant Function.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Region-Guided CycleGANs for Stain Transfer in Whole Slide Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Unsupervised Nuclei Segmentation Using Spatial Organization Priors.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Deep Learning based Multistep Registration Focusing on Regions of Change.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021
Deep Multi-Instance Learning Using Multi-Modal Data for Diagnosis of Lymphocytosis.
IEEE J. Biomed. Health Informatics, 2021

A Deep Multitask Learning Framework Coupling Semantic Segmentation and Fully Convolutional LSTM Networks for Urban Change Detection.
IEEE Trans. Geosci. Remote. Sens., 2021

Unsupervised Multistep Deformable Registration of Remote Sensing Imagery Based on Deep Learning.
Remote. Sens., 2021

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia.
Medical Image Anal., 2021

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.
CoRR, 2021

MICS : Multi-steps, Inverse Consistency and Symmetric deep learning registration network.
CoRR, 2021

Sparse convolutional context-aware multiple instance learning for whole slide image classification.
CoRR, 2021

Cancer Gene Profiling through Unsupervised Discovery.
CoRR, 2021

High-Particle Simulation of Monte-Carlo Dose Distribution with 3D ConvLSTMs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Weakly Supervised Pan-Cancer Segmentation Tool.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Exploring Deep Registration Latent Spaces.
Proceedings of the Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 2021

3d Unsupervised Kidney Graft Segmentation Based On Deep Learning And Multi-Sequence Mri.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Self-Supervised Representation Learning using Visual Field Expansion on Digital Pathology.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

A Joint Spatial and Magnification Based Attention Framework for Large Scale Histopathology Classification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification.
Proceedings of the MICCAI Workshop on Computational Pathology, 2021

Multi-Source Domain Adaptation via supervised contrastive learning and confident consistency regularization.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020
Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation.
Frontiers Comput. Neurosci., 2020

AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia.
CoRR, 2020

Self-supervised Nuclei Segmentation in Histopathological Images Using Attention.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Weakly Supervised Multiple Instance Learning Histopathological Tumor Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Deep Learning Based Registration Using Spatial Gradients and Noisy Segmentation Labels.
Proceedings of the Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data, 2020

2019
A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks.
Remote. Sens., 2019

U-ReSNet: Ultimate Coupling of Registration and Segmentation with Deep Nets.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Gene Expression High-Dimensional Clustering Towards a Novel, Robust, Clinically Relevant and Highly Compact Cancer Signature.
Proceedings of the Bioinformatics and Biomedical Engineering, 2019

Image Registration of Satellite Imagery with Deep Convolutional Neural Networks.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Data.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

A Multi-Task Deep Learning Framework Coupling Semantic Segmentation and Image Reconstruction for Very High Resolution Imagery.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Detailed Land Cover Mapping from Multitemporal Landsat-8 Data of Different Cloud Cover.
Remote. Sens., 2018

AtlasNet: Multi-atlas Non-linear Deep Networks for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Linear and Deformable Image Registration with 3D Convolutional Neural Networks.
Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018

Context Aware 3D CNNs for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

Deep patch-based priors under a fully convolutional encoder-decoder architecture for interstitial lung disease segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Stacked Encoder-Decoders for Accurate Semantic Segmentation of Very High Resolution Satellite Datasets.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017

Per city-block, density estimation at build-up areas from aerial RGB imagery with deep learning.
Proceedings of the Joint Urban Remote Sensing Event, 2017

Patch-based deep learning architectures for sparse annotated very high resolution datasets.
Proceedings of the Joint Urban Remote Sensing Event, 2017

Integrating edge/boundary priors with classification scores for building detection in very high resolution data.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017

2016
Graph-Based Registration, Change Detection, and Classification in Very High Resolution Multitemporal Remote Sensing Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

Simultaneous registration, segmentation and change detection from multisensor, multitemporal satellite image pairs.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2015
Building detection in very high resolution multispectral data with deep learning features.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

Simultaneous registration and change detection in multitemporal, very high resolution remote sensing data.
Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015

2014
Automatic Descriptor-Based Co-Registration of Frame Hyperspectral Data.
Remote. Sens., 2014


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