research
∙
11/07/2021
Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
Current treatment planning of patients diagnosed with brain tumor could ...
share
research
∙
10/01/2021
Algorithm Fairness in AI for Medicine and Healthcare
In the current development and deployment of many artificial intelligenc...
research
∙
09/03/2021
Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
Fast and accurate solutions of time-dependent partial differential equat...
research
∙
08/04/2021
Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning
The rapidly emerging field of deep learning-based computational patholog...
research
∙
09/21/2020
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
Deep Learning-based computational pathology algorithms have demonstrated...
research
∙
09/09/2020
Real-time Bayesian personalization via a learnable brain tumor growth model
Modeling of brain tumor dynamics has the potential to advance therapeuti...
research
∙
06/24/2020
Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary
Cancers of unknown primary (CUP), represent 1-3 enigmatic disease where ...
research
∙
04/22/2020
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective
Exploiting learning algorithms under scarce data regimes is a limitation...
research
∙
10/08/2019
Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
Fast and accurate solution of time-dependent partial differential equati...
research
∙
07/01/2019
Neural parameters estimation for brain tumor growth modeling
Understanding the dynamics of brain tumor progression is essential for o...
research
∙
01/13/2019
The Liver Tumor Segmentation Benchmark (LiTS)
In this work, we report the set-up and results of the Liver Tumor Segmen...
research
∙
11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
research
∙
07/02/2018
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
research
∙
07/02/2018
Personalized Radiotherapy Design for Glioblastoma Using Mathematical Models, Multimodal Scans and Bayesian Inference
Glioblastoma is a highly invasive brain tumor, whose cells infiltrate su...
research
∙
07/02/2018
Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration
Existing radiotherapy (RT) plans for brain tumors derive from population...
research
∙
04/07/2017
Automated Unsupervised Segmentation of Liver Lesions in CT scans via Cahn-Hilliard Phase Separation
The segmentation of liver lesions is crucial for detection, diagnosis an...
research
∙
02/20/2017