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Found 5 papers, 1 papers with code
POPE: Post Optimization Posterior Evaluation of Likelihood Free Models
We propose a post optimization posterior analysis that computes and visualizes all the models that can generate equally good or better simulation results, subject to constraints.
Automated Unsupervised Segmentation of Liver Lesions in CT scans via Cahn-Hilliard Phase Separation
The segmentation of liver lesions is crucial for detection, diagnosis and monitoring progression of liver cancer.
The Liver Tumor Segmentation Benchmark (LiTS)
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.
A multi-scale model of virus pandemic: Heterogeneous interactive entities in a globally connected world
This paper is devoted to the multidisciplinary modelling of a pandemic initiated by an aggressive virus, specifically the so-called \textit{SARS--CoV--2 Severe Acute Respiratory Syndrome, corona virus n. 2}.
Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans
This work proposes a method that uses Physics-Informed Neural Networks (PINNs) to estimate patient-specific parameters of a reaction-diffusion PDE model of GBM growth from a single 3D structural MRI snapshot.
