Sotirios Tsaftaris

Search results

• 2025

  Memcontrol: Mitigating memorization in medical diffusion models via automated parameter selection

  Dutt, R., Bohdal, O., Sanchez, P., Tsaftaris, S. A. & Hospedales, T., 8 Apr 2025, Proceedings of the 2025 IEEE Winter Conference on Applications of Computer Vision. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers, p. 4491-4501 11 p. (IEEE Winter Conference on Applications of Computer Vision).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File
• 2024

  BMFT: Achieving fairness via bias-based weight masking fine-tuning

  Xue, Y., Yan, J., Dutt, R., Haider, F., Liu, J., McDonagh, S. & Tsaftaris, S. A., 15 Jul 2024, (Accepted/In press) International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Training Data 100%
  • Substantial Amount 50%
  • Developing Model 50%
  • Postprocessing Method 50%
  • Sensitive Attribute 50%

• Parameter-efficient fine-tuning for medical image analysis: The missed opportunity

  Dutt, R., Ericsson, L., Sanchez, P., Tsaftaris, S. A. & Hospedales, T. M., 24 May 2024, Proceedings of Medical Imaging with Deep Learning. p. 1-20 20 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Image Analysis 100%
  • Missed Opportunity 100%
  • Medical Image 100%
  • Knowledge Transfer 100%
  • Artificial Intelligence 100%

• FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis

  Dutt, R., Bohdal, O., Tsaftaris, S. A. & Hospedales, T. M., 16 Jan 2024, (Accepted/In press) The Twelfth International Conference on Learning Representations. p. 1-24 24 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Medical Imaging 100%
  • Image Analysis 100%
  • Training Data 100%
  • Minimizes 100%
  • Medical Diagnosis 100%
• 2023

  Group Distributionally Robust Knowledge Distillation

  Vilouras, K., Liu, X., Sanchez, P., O’Neil, A. Q. & Tsaftaris, S. A., 15 Oct 2023, Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Proceedings. Cao, X., Ouyang, X., Xu, X., Rekik, I. & Cui, Z. (eds.). Springer, p. 234-242 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14349 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Knowledge Distillation 100%
  • Medical Imaging 50%
  • Optimization Technique 50%
  • Lower Performance 50%
  • Training Model 50%

• Compositional Representation Learning for Brain Tumour Segmentation

  Liu, X., Kascenas, A., Watson, H., Tsaftaris, S. A. & O’Neil, A. Q., 14 Oct 2023, Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Proceedings. Koch, L., Cardoso, M. J., Ferrante, E., Kamnitsas, K., Islam, M., Jiang, M., Rieke, N., Tsaftaris, S. A. & Yang, D. (eds.). Springer, p. 41-51 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14293 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Annotation 100%
  • Representation Learning 100%
  • Tumor Segmentation 100%
  • Unsupervised Learning 33%
  • Segmentation Performance 33%

• Debiasing Counterfactuals in the Presence of Spurious Correlations

  Kumar, A., Fathi, N., Mehta, R., Nichyporuk, B., Falet, J. P. R., Tsaftaris, S. & Arbel, T., 9 Oct 2023, Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023, Proceedings. Wesarg, S., Oyarzun Laura, C., Puyol Antón, E., King, A. P., Baxter, J. S. H., Erdt, M., Drechsler, K., Freiman, M., Chen, Y., Rekik, I., Eagleson, R., Feragen, A., Cheplygina, V., Ganz-Benjaminsen, M., Ferrante, E., Glocker, B., Moyer, D. & Petersen, E. (eds.). Springer, p. 276-286 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14242 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Image Synthesis 100%
  • Counter-factual 100%
  • Medical Imaging 50%
  • Deep Learning Model 50%
  • Distributionally Robust Optimization 50%

• Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction

  Du, Y., Xue, Y., Dharmakumar, R. & Tsaftaris, S. A., 9 Oct 2023, Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023, Proceedings. Wesarg, S., Oyarzun Laura, C., Puyol Antón, E., King, A. P., Baxter, J. S. H., Erdt, M., Drechsler, K., Freiman, M., Chen, Y., Rekik, I., Eagleson, R., Feragen, A., Cheplygina, V., Ganz-Benjaminsen, M., Ferrante, E., Glocker, B., Moyer, D. & Petersen, E. (eds.). Springer, p. 102-111 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14242 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Deep Learning Method 100%
  • Image Reconstruction 60%
  • Unfairness 20%
  • Image Quality 20%
  • Performance Model 20%

• SLX: Similarity Learning for X-Ray Screening and Robust Automated Disassembled Object Detection

  Dionelis, N., Jackson, R., Tsaftaris, S. A. & Yaghoobi Vaighan, M., 23 Jun 2023, 2023 International Joint Conference on Neural Networks (IJCNN). Institute of Electrical and Electronics Engineers

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Object Detection 100%
  • Anomaly Detection 100%
  • Baseline Model 100%
  • Residual Neural Network 100%
  • Learning Approach 100%

• FROB: Few-Shot ROBust Model for Joint Classification and Out-of-Distribution Detection

  Dionelis, N., Tsaftaris, S. A. & Yaghoobi Vaighan, M., 17 Mar 2023, (E-pub ahead of print) Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part III. Springer, Vol. 13715. p. 137-153 (Lecture Notes in Computer Science; vol. 13715).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Class Distribution 100%
  • Data Distribution 100%
  • Training Data 50%
  • Sample Distribution 50%
  • Independent Constant 50%

• Applying Disentanglement in the Medical Domain: An Introduction for the MAD Workshop

  Fragemann, J., Liu, X., Li, J., Tsaftaris, S. A., Egger, J. & Kleesiek, J., 1 Feb 2023, Medical Applications with Disentanglements - First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Proceedings. Fragemann, J., Li, J., Egger, J., Liu, X., Tsaftaris, S. A. & Kleesiek, J. (eds.). Springer, p. 3-11 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13823 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Medical Applications 100%
  • Deep Learning Method 100%
  • Deep Neural Network 100%
  • Space Representation 50%
  • Generative Model 50%

• HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information

  Liu, X., Thermos, S., Sanchez, P., O’Neil, A. Q. & Tsaftaris, S. A., 1 Feb 2023, Medical Applications with Disentanglements - First MICCAI Workshop, MAD 2022, Held in Conjunction with MICCAI 2022, Proceedings. Fragemann, J., Li, J., Egger, J., Liu, X., Tsaftaris, S. A. & Kleesiek, J. (eds.). Springer, p. 15-21 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13823 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Auxiliaries 100%
  • Unsupervised Learning 100%
• 2022

  CTR: Contrastive Training Recognition Classifier for Few-Shot Open-World Recognition

  Dionelis, N., Tsaftaris, S. A. & Yaghoobi Vaighan, M., 29 Nov 2022, (E-pub ahead of print) 2022 26th International Conference on Pattern Recognition (ICPR). Institute of Electrical and Electronics Engineers, p. 1792-1799 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Anomaly Detection 100%
  • Sample Distribution 66%
  • Knowledge Base 33%
  • Input Distribution 33%
  • Detect Anomaly 33%

• Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers

  Kumar, A., Hu, A., Nichyporuk, B., Falet, J. P. R., Arnold, D. L., Tsaftaris, S. & Arbel, T., 20 Nov 2022, Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery - 1st MICCAI Workshop, AIIIMA 2022, and 1st MICCAI Workshop, MIABID 2022, Held in Conjunction with MICCAI 2022, Proceedings. Kakileti, S. T., Manjunath, G., Gabrani, M., Rosen-Zvi, M., Braman, N., Schwartz, R. G., Frangi, A. F., Chung, P.-C., Weight, C. & Jagadish, V. (eds.). Springer, p. 113-124 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13602 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Process Synthesis 100%
  • Individual Level 100%
  • Image Synthesis 100%
  • Deep Learning Model 100%
  • Level Heterogeneity 100%

• What is Healthy? Generative Counterfactual Diffusion for Lesion Localization

  Sanchez, P., Kascenas, A., Liu, X., O’Neil, A. Q. & Tsaftaris, S. A., 8 Oct 2022, Deep Generative Models - 2nd MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Proceedings. Mukhopadhyay, A., Oksuz, I., Engelhardt, S., Zhu, D. & Yuan, Y. (eds.). Springer, p. 34-44 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13609 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • And-States 100%
  • Image Segmentation 100%
  • Difference Image 100%

• OMASGAN: Out-of-distribution Minimum Anomaly Score GAN for Anomaly Detection

  Dionelis, N., Tsaftaris, S. A. & Yaghoobi Vaighan, M., 23 Sept 2022, (E-pub ahead of print) 2022 Sensor Signal Processing for Defence Conference (SSPD). Institute of Electrical and Electronics Engineers

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Discriminator 100%
  • Supervised Learning 100%

• vMFNet: Compositionality Meets Domain-generalised Segmentation

  Liu, X., Thermos, S., Sanchez, P., O’Neil, A. & Tsaftaris, S. A., 17 Sept 2022, (E-pub ahead of print) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 : 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VII. Springer, Vol. 13437. p. 704–714 (Lecture Notes in Computer Science; vol. 13437).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

• Why patient data cannot be easily forgotten?

  Su, R., Liu, X. & Tsaftaris, S. A., 16 Sept 2022, (E-pub ahead of print) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VIII. Springer, Vol. 13438. p. 632–641 11 p. (Lecture Notes in Computer Science; vol. 13438).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Artificial Intelligence 100%
  • Performance Model 33%
  • Protection Regulation 33%
  • Data Protection 33%

• Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers

  Jacenków, G., O'Neil, A. & Tsaftaris, S. A., 26 Apr 2022, (E-pub ahead of print) 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). Institute of Electrical and Electronics Engineers, (International Symposium on Biomedical Imaging Proceedings; vol. 2022).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Experimental Result 100%
  • Classification Performance 100%
  • State-of-the-Art Method 100%
  • Image Classification 100%
  • Radiologist 100%
• 2021

  Few-Shot Adaptive Detection of Objects of Concern Using Generative Models with Negative Retraining

  Dionelis, N., Yaghoobi Vaighan, M. & Tsaftaris, S. A., 21 Dec 2021, (E-pub ahead of print) 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). Institute of Electrical and Electronics Engineers, p. 8

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Generative Adversarial Networks 100%
  • Generative Model 100%
  • Retraining 100%
  • Detection Method 100%
  • Large Data Set 28%

• Measuring the Biases and Effectiveness of Content-Style Disentanglement

  Liu, X., Thermos, S., Valvano, G., Chartsias, A., O'Neil, A. & Tsaftaris, S. A., 25 Nov 2021, The 32nd British Machine Vision Conference (BMVC). BMVA Press

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Task Performance 100%
  • Learning Objective 100%
  • Interpretability 25%
  • Performance Model 25%
  • Constraint Learning 25%

• Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation

  Nichyporuk, B., Cardinell, J., Szeto, J., Mehta, R., Tsaftaris, S., Arnold, D. L. & Arbel, T., 21 Sept 2021, Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health - 3rd MICCAI Workshop, DART 2021, and 1st MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Proceedings. Albarqouni, S., Cardoso, M. J., Dou, Q., Kamnitsas, K., Khanal, B., Rekik, I., Rieke, N., Sheet, D., Tsaftaris, S., Xu, D. & Xu, Z. (eds.). Springer, p. 101-111 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12968 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Widespread Adoption 100%
  • Lesion Segmentation 100%
  • Big Data 100%
  • Dataset Source 100%
  • Tumor Segmentation 100%

• Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning

  Valvano, G., Leo, A. & Tsaftaris, S. A., 21 Sept 2021, Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health: 3rd MICCAI Workshop, DART 2021, and 1st MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Proceedings. Albarqouni, S., Cardoso, M. J., Dou, Q., Kamnitsas, K., Khanal, B., Rekik, I., Rieke, N., Sheet, D., Tsaftaris, S., Xu, D. & Xu, Z. (eds.). Springer, p. 14-24 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12968 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Annotation 100%
  • Learning System 100%
  • Supervised Learning 100%
  • Art Performance 50%
  • Attention (Machine Learning) 50%

• Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation

  Liu, X., Thermos, S., O'Neil, A. & Tsaftaris, S. A., 21 Sept 2021, (E-pub ahead of print) Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II. Springer, Vol. 12902. p. 307-317 (Lecture Notes in Computer Science; vol. 12902).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Image Segmentation 100%
  • Meta-Learning 100%
  • Generalization Performance 60%
  • Learning Approach 40%
  • Annotation 20%

• Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training

  Valvano, G., Leo, A. & Tsaftaris, S. A., 21 Sept 2021, Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health: Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Albarqouni, S., Cardoso, M. J., Dou, Q., Kamnitsas, K., Khanal, B., Rekik, I., Rieke, N., Sheet, D., Tsaftaris, S., Xu, D. & Xu, Z. (eds.). Springer, p. 68-78 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12968 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Data Distribution 100%
  • Performance Model 100%
  • Life Cycle 100%
  • Data Pair 100%
  • Test Time 100%

• Disentangled Representations for Domain-generalized Cardiac Segmentation

  Liu, X., Thermos, S., Chartsias, A., O'Neil, A. & Tsaftaris, S., 29 Jan 2021, (E-pub ahead of print) STACOM: International Workshop on Statistical Atlases and Computational Models of the Heart: Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges. Springer, p. 187-195 (Lecture Notes in Computer Science; vol. 12592).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Image Segmentation 100%
  • Generalization Ability 100%
  • Domain Adaptation 100%
  • Medical Data 100%
  • Original Sample 100%
• 2020

  Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling

  Jiang, H., Wang, C., Chartsias, A. & Tsaftaris, S., 21 Dec 2020, (E-pub ahead of print) MyoPS: Myocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge: Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images. Springer, p. 68-81 (Lecture Notes in Computer Science ; vol. 12554).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  File

  • U-Net 100%
  • Automatic Segmentation 33%
  • Segmentation Performance 33%
  • Training Example 33%
  • Multimodal Information 33%

• Tail of Distribution GAN (TailGAN): Generative-Adversarial-Network-Based Boundary Formation

  Dionelis, N., Yaghoobi Vaighan, M. & Tsaftaris, S., 30 Nov 2020, 2020 Sensor Signal Processing for Defence Conference (SSPD). Institute of Electrical and Electronics Engineers, p. 1-5 5 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Data Distribution 100%
  • Generative Adversarial Networks 100%
  • Tail 100%
  • X Ray 100%
  • Probability Theory 33%

• Boundary Of Distribution Support Generator (BDSG): Sample Generation On The Boundary

  Dionelis, N., Yaghoobi, M. & Tsaftaris, S. A., 30 Sept 2020, 2020 IEEE International Conference on Image Processing (ICIP). Institute of Electrical and Electronics Engineers, p. 803-807 5 p. 9191341

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Residual Network 100%
  • Residual Neural Network 100%
  • Residuals 66%
  • Multimodal Distribution 66%
  • Generative Adversarial Networks 66%

• Semi-supervised Pathology Segmentation with Disentangled Representations

  Jiang, H., Chartsias, A., Zhang, X., Papanastasiou, G., Semple, S., Dweck, M., Semple, D., Dharmakumar, R. & Tsaftaris, S., 26 Sept 2020, (E-pub ahead of print) DART: MICCAI Workshop on Domain Adaptation and Representation Transfer : Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. Springer, p. 62-72 (Lecture Notes in Computer Science; vol. 12444).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Annotation 100%
  • Magnetic Resonance Imaging 100%
  • Myocardial Infarction 100%
  • Semisupervised Learning 33%
  • Unlabeled Data 33%
• 2019

  Ontological attention ensembles for capturing semantic concepts in ICD code prediction from clinical text

  Falis, M., Pajak, M., Lisowska, A., Schrempf, P., Deckers, L., Mikhael, S., Tsaftaris, S. & O'Neil, A., 1 Nov 2019, Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019). Hong Kong: Association for Computational Linguistics, p. 168-177 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Ontology 100%
  • Semantic Concept 100%
  • Attention (Machine Learning) 50%
  • Leading Concept 50%
  • Lowest Common Denominator 50%

• Consistent Brain Ageing Synthesis

  Alzheimers Disease Neuroimaging Initiative, 13 Oct 2019, Medical Image Computing and Computer Assisted Intervention -MICCAI 2019: 22nd International Conference, Shenzhen, China 13-17 October 2019. Springer, (Lecture Notes in Computer Science).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Subject Identity 100%
  • Adversarial Machine Learning 100%
  • Continuous Variable 100%
  • Joint Distribution 100%

• Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

  Valvano, G., Chartsias, A., Leo, A. & Tsaftaris, S. A., 13 Oct 2019, (E-pub ahead of print) Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data: First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings. Springer, Vol. 11795.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Appearance Characteristic 100%
  • Phase Difference 100%

• Multimodal cardiac segmentation using disentangled representations

  Chartsias, A., Papanastasiou, G., Wang, C., Stirrat, C., Semple, S., Newby, D., Dharmakumar, R. & Tsaftaris, S., 9 Aug 2019, (Accepted/In press) STACOM: Statistical Atlases and Computational Models of the Heart.. Springer

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Annotation 100%
  • Image Sequence 100%
  • Semisupervised Model 100%
  • Transformer Network 100%
  • Magnetic Resonance Imaging 100%

• Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization

  Xia, T., Chartsias, A. & Tsaftaris, S., 10 Jul 2019, Proceedings of Machine Learning Research: Medical Imaging Deep Learning. Vol. 102.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Synthesis 100%
  • Factorization 100%
  • Segmentation 50%
  • Image Synthesis 50%
  • Networks 50%

• Adversarial Large-Scale Root Gap Inpainting

  Chen, H., Valerio Giuffrida, M., Doerner, P. & Tsaftaris, S. A., 20 Jun 2019, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Computer Vision Foundation

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

• Leaf Counting Without Annotations Using Adversarial Unsupervised Domain Adaptation

  Valerio Giuffrida, M., Dobrescu, A., Doerner, P. & Tsaftaris, S. A., 20 Jun 2019, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Computer Vision Foundation

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

• Understanding Deep Neural Networks for Regression in Leaf Counting

  Dobrescu, A., Valerio Giuffrida, M. & Tsaftaris, S. A., 1 Jun 2019, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Computer Vision Foundation

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access
• 2018

  Deep Multi-Class Segmentation Without Ground-Truth Labels

  Joyce, T., Chartsias, A. & Tsaftaris, S., Jul 2018, Medical Imaging with Deep Learning: Amsterdam. Amsterdam

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Segmentation Task 100%
  • Adversarial Machine Learning 100%
  • segmentation algorithm 100%

• Joint myocardial registration and segmentation of cardiac BOLD MRI

  Oksuz, I., Dharmakumar, R. & Tsaftaris, S. A., 15 Mar 2018, Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges - 8th International Workshop, STACOM 2017, Revised Selected Papers. Springer, p. 12-20 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10663 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Dictionary Learning 100%
  • Joints (Structural Components) 100%
  • Medical Imaging 50%
  • Sparse Representation 50%
  • Training Image 50%

• Leveraging multiple datasets for deep leaf counting

  Dobrescu, A., Giuffrida, M. V. & Tsaftaris, S., 23 Jan 2018, (E-pub ahead of print) International Conference on Computer Vision: Computer Vision Problems in Plant Phenotyping (workshop). Institute of Electrical and Electronics Engineers, 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Annotation 100%
  • Deep Learning Method 100%
  • Regression Problem 50%
  • Deep Neural Network 50%
  • Instance Segmentation 50%
• 2017

  Adversarial Image Synthesis for Unpaired Multi-Modal Cardiac Data

  Chartsias, A., Joyce, T., Dharmakumar, R. & Tsaftaris, S. A., 26 Sept 2017, Simulation and Synthesis in Medical Imaging: Second International Workshop, SASHIMI 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10, 2017, Proceedings. Tsaftaris, S., Gooya, A., Frangi, A. & Prince, J. (eds.). 1 ed. Springer, Vol. 10557. p. 3-13 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10557 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Image Synthesis 100%
  • Synthetic Data 100%
  • Neural Network 33%
  • Synthetic Image 33%
  • Training Data 33%

• Robust Multi-Modal MR Image Synthesis

  Joyce, T., Chartsias, A. & Tsaftaris, S., 4 Sept 2017, Medical Image Computing and Computer-Assisted Intervention-MICCAI 2017 : 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III. Springer, p. 347-355 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10435 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Input Multi 100%
  • Image Synthesis 100%
  • Neural Network 100%
  • Test Time 50%
  • Input Data 50%

• ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network

  Giuffrida, M. V., Scharr, H. & Tsaftaris, S., 2017, (Accepted/In press) International Conference on Computer Vision: Computer Vision Problems in Plant Phenotyping Workshop. Institute of Electrical and Electronics Engineers, 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • Generative Adversarial Networks 100%
  • Training Data 100%
  • Arabidopsis 100%
  • Rosette Formation 100%
  • State of the Art 100%
• 2016

  Rotation-Invariant Restricted Boltzmann Machine Using Shared Gradient Filters

  Tsaftaris, S. & Giuffrida, M. V., 6 Sept 2016, Artificial Neural Networks and Machine Learning – ICANN 2016: 25th International Conference on Artificial Neural Networks, Barcelona, Spain, September 6-9, 2016, Proceedings, Part II. Springer, (Theoretical Computer Science and General Issues).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

• Whole Image Synthesis using a Deep Encoder-Decoder Network

  Sevetlidis, V., Giuffrida, M. V. & Tsaftaris, S., 10 Aug 2016, Simulation and Synthesis in Medical Imaging: First International Workshop, SASHIMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Springer

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

• Classification-aware distortion metric for HEVC intra coding

  Minervini, M. & Tsaftaris, S. A., 25 Apr 2016, 2015 Visual Communications and Image Processing, VCIP 2015. Institute of Electrical and Electronics Engineers, 7457877

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Geometric Interpretation 100%

• Supervised learning of functional maps for infarct classification

  Mukhopadhyay, A., Oksuz, I. & Tsaftaris, S. A., 9 Jan 2016, (E-pub ahead of print) Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges - 6th International Workshop, STACOM 2015 Held in Conjunction with MICCAI 2015, Revised Selected Papers. Springer, p. 162-170 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9534).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Training Data 100%
  • Singular Value 100%
  • Cross-Validation 100%
  • SVM Model 100%
  • Singular Value Decomposition 100%
• 2015

  An interactive tool for semi-automated leaf annotation

  Minervini, M., Giuffrida, M. V. & Tsaftaris, S., 1 Sept 2015, Proceedings of the Computer Vision Problems in Plant Phenotyping (CVPPP). S. A. Tsaftaris, H. S. & Pridmore, T. (eds.). BMVA Press, p. 6.1-6.13

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Learning to Count Leaves in Rosette Plants

  Giuffrida, M. V., Minervini, M. & Tsaftaris, S., 1 Sept 2015, Proceedings of the Computer Vision Problems in Plant Phenotyping (CVPPP). S. A. Tsaftaris, H. S. & Pridmore, T. (eds.). BMVA Press, p. 1.1-1.13

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution