Mireia Crispin-Ortuzar

According to our database, Mireia Crispin-Ortuzar authored at least 15 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Evaluating Foundation Models with Pathological Concept Learning for Kidney Cancer.

Shangqi Gao, Sihan Wang, Yibo Gao, Boming Wang, Xiahai Zhuang, Anne Warren, Grant Stewart, James O. Jones, Mireia Crispin-Ortuzar

CoRR, September, 2025

Multi-task deep learning for automatic image segmentation and treatment response assessment in metastatic ovarian cancer.

Bevis Drury, Inês Prata Machado, Zeyu Gao, Thomas Buddenkotte, Golnar Mahani, Gabriel Funingana, Marika Reinius, Cathal McCague, Ramona Woitek, Anju Sahdev, Evis Sala, James D. Brenton, Mireia Crispin-Ortuzar

Int. J. Comput. Assist. Radiol. Surg., September, 2025

Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancer.

Daniël Boeke, Cedrik Blommestijn, Rebecca Wray, Kalina Chupetlovska, Shangqi Gao, Zeyu Gao, Regina G. H. Beets-Tan, Mireia Crispin-Ortuzar, James O. Jones, Wilson Silva, Inês Prata Machado

CoRR, August, 2025

ST-Prompt Guided Histological Hypergraph Learning for Spatial Gene Expression Prediction.

Yi Niu, Jiashuai Liu, Yingkang Zhan, Jiangbo Shi, Di Zhang, Inês Machado, Mireia Crispin-Ortuzar, Chen Li, Zeyu Gao

CoRR, March, 2025

Probabilistic Integration of Renal Cancer Radiology and Pathology Using Graph Neural Networks.

Shangqi Gao, Shangde Gao, Inês Machado, Mireia Crispin-Ortuzar

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

2024

CTARR: A fast and robust method for identifying anatomical regions on CT images via atlas registration.

Thomas Buddenkotte, Roland Opfer, Julia Krüger, Alessa Hering, Mireia Crispin-Ortuzar

CoRR, 2024

CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival Analysis.

William Knottenbelt, Zeyu Gao, Rebecca Wray, Woody Zhidong Zhang, Jiashuai Liu, Mireia Crispin-Ortuzar

CoRR, 2024

A Self-supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer.

Inês Prata Machado, Anna Reithmeir, Fryderyk Victor Kögl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James D. Brenton, Julia A. Schnabel, Mireia Crispin

Proceedings of the Biomedical Image Registration - 11th International Workshop, 2024

Automated Small Kidney Cancer Detection in Non-Contrast Computed Tomography.

William McGough, Thomas Buddenkotte, Stephan Ursprung, Zeyu Gao, Grant Stewart, Mireia Crispin-Ortuzar

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Shallow-Deep Synergy: Boosting Cross-Domain Generalization in Histopathological Image Segmentation.

Xiangyu Wang, Weiheng Su, Yuxing Dong, Yang Li, Xianli Zhang, Tieliang Gong, Inês Prata Machado, Mireia Crispin-Ortuzar, Chen Li, Zeyu Gao

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023

Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation.

Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague, James D. Brenton, Ozan Öktem, Evis Sala, Leonardo Rundo

Comput. Biol. Medicine, September, 2023

Live Demonstration: An AI Driven Multiplexed Diagnostic Platform for Improving Cancer Care.

Saif S. Ahmad, Ama Frimpong, Mireia Crispin-Ortuzar, Nicole E. Weckman

Proceedings of the 2023 IEEE SENSORS, Vienna, Austria, October 29 - Nov. 1, 2023, 2023

2022

Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation.

Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar, Ramona Woitek, Cathal McCague, James D. Brenton, Ozan Öktem, Evis Sala, Leonardo Rundo

CoRR, 2022

2021

Predictive Modelling of Highly Multiplexed Tumour Tissue Images by Graph Neural Networks.

Paula Martin-Gonzalez, Mireia Crispin-Ortuzar, Florian Markowetz

Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data, 2021

2020

Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering.

Leonardo Rundo, Lucian Beer, Stephan Ursprung, Paula Martin-Gonzalez, Florian Markowetz, James D. Brenton, Mireia Crispin-Ortuzar, Evis Sala, Ramona Woitek

Comput. Biol. Medicine, 2020