Jana Lipkova | DeepAI

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∙ 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 ...

35 Ivan Ezhov, et al. ∙

∙ 10/01/2021

Algorithm Fairness in AI for Medicine and Healthcare

In the current development and deployment of many artificial intelligenc...

0 Richard J. Chen, et al. ∙

∙ 09/03/2021

Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations

Fast and accurate solutions of time-dependent partial differential equat...

4 Suprosanna, et al. ∙

∙ 08/04/2021

Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learning

The rapidly emerging field of deep learning-based computational patholog...

17 Richard J. Chen, et al. ∙

∙ 09/21/2020

Federated Learning for Computational Pathology on Gigapixel Whole Slide Images

Deep Learning-based computational pathology algorithms have demonstrated...

29 Ming Y. Lu, et al. ∙

∙ 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...

1 Ivan Ezhov, et al. ∙

∙ 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 ...

0 Ming Y. Lu, et al. ∙

∙ 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...

8 Ahmad B Qasim, et al. ∙

∙ 10/08/2019

Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee

Fast and accurate solution of time-dependent partial differential equati...

1 Suprosanna, et al. ∙

∙ 07/01/2019

Neural parameters estimation for brain tumor growth modeling

Understanding the dynamics of brain tumor progression is essential for o...

4 Ivan Ezhov, et al. ∙

∙ 01/13/2019

The Liver Tumor Segmentation Benchmark (LiTS)

In this work, we report the set-up and results of the Liver Tumor Segmen...

8 Patrick Bilic, et al. ∙

∙ 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...

0 Spyridon Bakas, et al. ∙

∙ 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...

0 Jana Lipkova, et al. ∙

∙ 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...

0 Jana Lipkova, et al. ∙

∙ 07/02/2018

Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration

Existing radiotherapy (RT) plans for brain tumors derive from population...

0 Jana Lipkova, et al. ∙

∙ 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...

0 Jana Lipkova, et al. ∙

∙ 02/20/2017

Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks

Automatic segmentation of the liver and hepatic lesions is an important ...

0 Patrick Ferdinand Christ, et al. ∙

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