Spyridon Bakas
Orcid: 0000-0001-8734-6482
According to our database1,
Spyridon Bakas
authored at least 69 papers
between 2011 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
Nat. Mac. Intell., July, 2023
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.
Medical Image Anal., 2023
Framing image registration as a landmark detection problem for better representation of clinical relevance.
CoRR, 2023
Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting.
CoRR, 2023
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.
CoRR, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
CoRR, 2022
Artificial intelligence-based locoregional markers of brain peritumoral microenvironment.
CoRR, 2022
CoRR, 2022
CoRR, 2022
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation.
CoRR, 2022
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
Leveraging 2D Deep Learning ImageNet-trained Models for Native 3D Medical Image Analysis.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
2021
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
CoRR, 2021
The Brain Tumor Sequence Registration Challenge: Establishing Correspondence between Pre-Operative and Follow-up MRI scans of diffuse glioma patients.
CoRR, 2021
The University of California San Francisco Preoperative Diffuse Glioma (UCSF-PDGM) MRI Dataset.
CoRR, 2021
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.
CoRR, 2021
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient.
CoRR, 2021
GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging.
CoRR, 2021
Comput. Medical Imaging Graph., 2021
Classification of Infection and Ischemia in Diabetic Foot Ulcers Using VGG Architectures.
Proceedings of the Diabetic Foot Ulcers Grand Challenge - Second Challenge, 2021
Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021
2020
IEEE Trans. Medical Imaging, 2020
Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.
NeuroImage, 2020
Longitudinal brain tumor segmentation prediction in MRI using feature and label fusion.
Biomed. Signal Process. Control., 2020
Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols.
Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020
2019
Multi-Disease Segmentation of Gliomas and White Matter Hyperintensities in the BraTS Data Using a 3D Convolutional Neural Network.
Frontiers Comput. Neurosci., 2019
Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients.
Frontiers Comput. Neurosci., 2019
Accurate and Robust Alignment of Variable-stained Histologic Images Using a General-purpose Greedy Diffeomorphic Registration Tool.
CoRR, 2019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms.
CoRR, 2019
Non-invasive transcriptomic classification of de novo Glioblastoma patients through multivariate quantitative analysis of baseline preoperative multimodal magnetic resonance imaging.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach.
NeuroImage, 2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
CoRR, 2018
Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Patient-Specific Registration of Pre-operative and Post-recurrence Brain Tumor MRI Scans.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis and machine learning techniques.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Fast semi-automatic segmentation of focal liver lesions in contrast-enhanced ultrasound, based on a probabilistic model.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2017
Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
2016
Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016
2015
GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015
2014
Computer-aided localisation, segmentation and quantification of focal liver lesions in contrast-enhanced ultrasound.
PhD thesis, 2014
Fast Segmentation of Focal Liver Lesions in Contrast-Enhanced Ultrasound Data.
Proceedings of the Medical Image Understanding and Analysis, 2014
Automatic Identification and Localisation of Potential Malignancies in Contrast-Enhanced Ultrasound Liver Scans Using Spatio-Temporal Features.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2014
Making the Best Use of Fifty (or More) Shades of Gray: Intelligent Contrast Optimisation for Image Segmentation in False-Colour Video.
Proceedings of the 2014 International Conference on Intelligent Environments, Shanghai, China, June 30, 2014
2013
Spot the Best Frame: Towards Intelligent Automated Selection of the Optimal Frame for Initialisation of Focal Liver Lesion Candidates in Contrast-Enhanced Ultrasound Video Sequences.
Proceedings of the 9th International Conference on Intelligent Environments, 2013
2012
Proceedings of the Advances in Visual Computing - 8th International Symposium, 2012
2011
Localisation and characterisation of focal liver lesions using contrast-enhanced ultrasonographic visual cues.
Proceedings of the Medical Image Understanding and Analysis, 2011