[HTML][HTML] Optimizing neuro-oncology imaging: a review of deep learning approaches for glioma imaging
MM Shaver, PA Kohanteb, C Chiou, MD Bardis… - Cancers, 2019 - mdpi.com
Radiographic assessment with magnetic resonance imaging (MRI) is widely used to
characterize gliomas, which represent 80% of all primary malignant brain tumors. Unfortunately, …
characterize gliomas, which represent 80% of all primary malignant brain tumors. Unfortunately, …
Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas
…, BD Weinberg, M Bardis, M Khy… - American Journal …, 2018 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: The World Health Organization has recently placed new
emphasis on the integration of genetic information for gliomas. While tissue sampling remains …
emphasis on the integration of genetic information for gliomas. While tissue sampling remains …
[HTML][HTML] Applications of artificial intelligence to prostate multiparametric MRI (mpMRI): current and emerging trends
Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric
magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion …
magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion …
Viscosity solutions: a primer
M Bardi, MG Crandall, LC Evans, HM Soner… - … at the 2nd Session of the …, 1997 - Springer
… Other boundary conditions appear in the contributions of Bardi [2] and Soner [34] in an
essential way. In addition to the references they give, the reader may refer for example to [12, …
essential way. In addition to the references they give, the reader may refer for example to [12, …
[BOOK][B] Optimal control and viscosity solutions of Hamilton-Jacobi-Bellman equations
M Bardi, IC Dolcetta - 1997 - Springer
The purpose of the present book is to offer an up-to-date account of the theory of viscosity
solutions of first order partial differential equations of Hamilton-Jacobi type and its applications …
solutions of first order partial differential equations of Hamilton-Jacobi type and its applications …
A 3D-2D hybrid U-net convolutional neural network approach to prostate organ segmentation of multiparametric MRI
… Meyer A, Mehrtash A, Rak M, et al. Automatic high resolution segmentation of the prostate
from multi-planar MRI. In: 2018 IEEE 15th International … Bardis contributed equally to this work. …
from multi-planar MRI. In: 2018 IEEE 15th International … Bardis contributed equally to this work. …
Segmentation of the prostate transition zone and peripheral zone on MR images with deep learning
M Bardis, R Houshyar, C Chantaduly… - Radiology: Imaging …, 2021 - pubs.rsna.org
Purpose To develop a deep learning model to delineate the transition zone (TZ) and peripheral
zone (PZ) of the prostate on MR images. Materials and Methods This retrospective study …
zone (PZ) of the prostate on MR images. Materials and Methods This retrospective study …
[PDF][PDF] On Hopf's formulas for solutions of Hamilton-Jacobi equations
M Bardi, LC Evans - Nonlinear Analysis: Theory, Methods & …, 1984 - elearning.unipd.it
U,+ H (Du)= 0(1.1) in RT”= W” x (0, 2). This PDE admits a particularly simple class of
solutions, namely the linear functions cu* xM (a)+/3(1.2) for fixed CY EW”,/3 E W. Hopf in [g] …
solutions, namely the linear functions cu* xM (a)+/3(1.2) for fixed CY EW”,/3 E W. Hopf in [g] …
Microscopic investigation of the atomization and mixing processes of diesel sprays injected into high pressure and temperature environments
Atomization and mixing of sprays are key parameters to successfully describe and predict
combustion in direct-injection engines. Understanding these processes at the conditions most …
combustion in direct-injection engines. Understanding these processes at the conditions most …
[HTML][HTML] Deep learning with limited data: organ segmentation performance by U-Net
(1) Background: The effectiveness of deep learning artificial intelligence depends on data
availability, often requiring large volumes of data to effectively train an algorithm. However, few …
availability, often requiring large volumes of data to effectively train an algorithm. However, few …