Cargando…

BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease

Introduction: Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Non-invasive neuroimaging techniques, such as time-of-flight (TOF) magnetic resonance angiography (MRA) imaging are applied in the clinical routine to depict arteries. They...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hilbert, Adam, Madai, Vince I., Akay, Ela M., Aydin, Orhun U., Behland, Jonas, Sobesky, Jan, Galinovic, Ivana, Khalil, Ahmed A., Taha, Abdel A., Wuerfel, Jens, Dusek, Petr, Niendorf, Thoralf, Fiebach, Jochen B., Frey, Dietmar, Livne, Michelle
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2020
Materias:	Artificial Intelligence
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861225/ https://www.ncbi.nlm.nih.gov/pubmed/33733207 http://dx.doi.org/10.3389/frai.2020.552258

Ejemplares similares

Anatomical labeling of intracranial arteries with deep learning in patients with cerebrovascular disease
por: Hilbert, Adam, et al.
Publicado: (2022)

A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease
por: Frey, Dietmar, et al.
Publicado: (2021)

Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy
por: Behland, Jonas, et al.
Publicado: (2023)

Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks
por: Kossen, Tabea, et al.
Publicado: (2022)

A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease
por: Livne, Michelle, et al.
Publicado: (2019)

On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking
por: Aydin, Orhun Utku, et al.
Publicado: (2021)

An evaluation of performance measures for arterial brain vessel segmentation
por: Aydin, Orhun Utku, et al.
Publicado: (2021)

Correction: On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking
por: Aydin, Orhun Utku, et al.
Publicado: (2022)

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease
por: Kossen, Tabea, et al.
Publicado: (2023)

Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome
por: Zihni, Esra, et al.
Publicado: (2020)

Rapid Parametric Mapping of the Longitudinal Relaxation Time T(1) Using Two-Dimensional Variable Flip Angle Magnetic Resonance Imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla
por: Dieringer, Matthias A., et al.
Publicado: (2014)

Building One-Shot Semi-Supervised (BOSS) Learning Up to Fully Supervised Performance
por: Smith, Leslie N., et al.
Publicado: (2022)

A deep crowd density classification model for Hajj pilgrimage using fully convolutional neural network
por: Bhuiyan, Md Roman, et al.
Publicado: (2022)

A fully automated approach involving neuroimaging and deep learning for Parkinson’s disease detection and severity prediction
por: Erdaş, Çağatay Berke, et al.
Publicado: (2023)

An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography
por: Burke, Jamie, et al.
Publicado: (2023)

Segmentation of Lung Nodules on CT Images Using a Nested Three-Dimensional Fully Connected Convolutional Network
por: Kido, Shoji, et al.
Publicado: (2022)

Fully Automated Segmentation of Human Eyeball Using Three-Dimensional U-Net in T2 Magnetic Resonance Imaging
por: Yang, Jin-Ju, et al.
Publicado: (2023)

A Deep Learning–Based Fully Automated Program for Choroidal Structure Analysis Within the Region of Interest in Myopic Children
por: Xuan, Meng, et al.
Publicado: (2023)

COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans
por: Heidarian, Shahin, et al.
Publicado: (2021)

AlphaDDA: strategies for adjusting the playing strength of a fully trained AlphaZero system to a suitable human training partner
por: Fujita, Kazuhisa
Publicado: (2022)

Ultrahigh-Field MRI in Human Ischemic Stroke – a 7 Tesla Study
por: Madai, Vince I., et al.
Publicado: (2012)

DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation
por: Bui, Vy, et al.
Publicado: (2022)

Artificial intelligence for analyzing orthopedic trauma radiographs: Deep learning algorithms—are they on par with humans for diagnosing fractures?
por: Olczak, Jakub, et al.
Publicado: (2017)

Design Characteristics of Studies Reporting the Performance of Artificial Intelligence Algorithms for Diagnostic Analysis of Medical Images: Results from Recently Published Papers
por: Kim, Dong Wook, et al.
Publicado: (2019)

Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery
por: Loftus, Tyler J., et al.
Publicado: (2020)

A Frequency-Domain Machine Learning Method for Dual-Calibrated fMRI Mapping of Oxygen Extraction Fraction (OEF) and Cerebral Metabolic Rate of Oxygen Consumption (CMRO(2))
por: Germuska, Michael, et al.
Publicado: (2020)

Artificial intelligence-guided tissue analysis combined with immune infiltrate assessment predicts stage III colon cancer outcomes in PETACC08 study
por: Reichling, Cynthia, et al.
Publicado: (2020)

Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations
por: Comess, Saskia, et al.
Publicado: (2020)

On the Adaptability of Recurrent Neural Networks for Real-Time Jazz Improvisation Accompaniment
por: Kritsis, Kosmas, et al.
Publicado: (2021)

Case Report: Utilizing AI and NLP to Assist with Healthcare and Rehabilitation During the COVID-19 Pandemic
por: Carriere, Jay, et al.
Publicado: (2021)

A survey on exponential random graph models: an application perspective
por: Ghafouri, Saeid, et al.
Publicado: (2020)

Effects of data count and image scaling on Deep Learning training
por: Hirahara, Daisuke, et al.
Publicado: (2020)

Deep learning based Sequential model for malware analysis using Windows exe API Calls
por: Catak, Ferhat Ozgur, et al.
Publicado: (2020)

Data augmentation based malware detection using convolutional neural networks
por: Catak, Ferhat Ozgur, et al.
Publicado: (2021)

Leveraging aspect phrase embeddings for cross-domain review rating prediction
por: Jiang, Aiqi, et al.
Publicado: (2019)

Conformational Changes of the Receptor Binding Domain of SARS-CoV-2 Spike Protein and Prediction of a B-Cell Antigenic Epitope Using Structural Data
por: Khare, Sangeeta, et al.
Publicado: (2021)

A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework
por: Bari, Bifta Sama, et al.
Publicado: (2021)

Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain
por: Tabares-Soto, Reinel, et al.
Publicado: (2021)

Classification model for accuracy and intrusion detection using machine learning approach
por: Agarwal, Arushi, et al.
Publicado: (2021)

Syntactic- and morphology-based text augmentation framework for Arabic sentiment analysis
por: Duwairi, Rehab, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_p8d275ci4efdtthal9p0gkod1a