About: Attention U-Net Based Adversarial Architectures for Chest X-ray Lung Segmentation

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Attention U-Net Based Adversarial Architectures for Chest X-ray Lung Segmentation Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Attention U-Net Based Adversarial Architectures for Chest X-ray Lung Segmentation
Creator	Gaál, Gusztáv Lukács, András Maga, Balázs
Source	ArXiv
abstract	Chest X-ray is the most common test among medical imaging modalities. It is applied for detection and differentiation of, among others, lung cancer, tuberculosis, and pneumonia, the last with importance due to the COVID-19 disease. Integrating computer-aided detection methods into the radiologist diagnostic pipeline, greatly reduces the doctors' workload, increasing reliability and quantitative analysis. Here we present a novel deep learning approach for lung segmentation, a basic, but arduous task in the diagnostic pipeline. Our method uses state-of-the-art fully convolutional neural networks in conjunction with an adversarial critic model. It generalized well to CXR images of unseen datasets with different patient profiles, achieving a final DSC of 97.5% on the JSRT dataset.
has issue date	2020-03-23(xsd:dateTime)
has license	arxiv
sha1sum (hex)	7c9af320dc827a1805f627f7da197955e5de1643
resource representing a document's title	Attention U-Net Based Adversarial Architectures for Chest X-ray Lung Segmentation
resource representing a document's body	covid:7c9af320dc827a1805f627f7da197955e5de1643#body_text
is schema:about of	named entity 'Chest X-ray' named entity 'NOVEL' named entity 'GREATLY' named entity 'OUR' named entity 'modalities' named entity 'reliability' named entity 'patient' named entity 'Architectures' named entity 'pneumonia' named entity 'lung' named entity 'U-Net' named entity 'cross-entropy' named entity 'tuberculosis' named entity 'medical imaging' named entity 'uniform distribution' named entity 'ROI' named entity 'lung' named entity 'histogram equalization' named entity 'CDF' named entity 'pixel' named entity 'chest X-rays' named entity 'computed tomography' named entity 'pixel' named entity 'neural-network' named entity 'lung' named entity 'X-rays' named entity 'pixel' named entity 'pixels' named entity 'TensorFlow' named entity 'vanilla' named entity 'U-Net' named entity 'ground truth' named entity 'tuberculosis' named entity 'pixels' named entity 'lesion' named entity 'X-rays' named entity 'overline' named entity 'MRI' named entity 'lung' named entity 'X-ray' named entity 'lung' named entity 'CLAHE' named entity 'U-Net' named entity 'Stochastic Gradient Descent' named entity 'CNN' named entity 'grayscale' named entity 'pixel' named entity 'lung' named entity 'neural networks' named entity 'National Health Service' named entity 'diagnostic ultrasound' named entity 'early diagnosis' named entity 'ROIs' named entity 'Convolutional Networks' named entity 'ribcage' named entity 'grayscale' named entity 'adversarial techniques' named entity 'Radiological Technology' named entity 'X-rays' named entity 'pixel' named entity 'Tversky index' named entity 'ROI' named entity 'CNN' named entity 'pixel' named entity 'pixel' named entity 'probability' named entity 'U-Net' named entity 'X-ray' named entity 'convolutional networks' named entity 'plain X-ray' named entity 'U-Net' named entity 'ith' named entity 'DSC' named entity 'chest X-ray' named entity 'lung' named entity 'cardiothoracic ratio' named entity 'pixel' named entity 'histogram' named entity 'CLAHE' named entity 'adaptive histogram equalization' named entity 'high resolution' named entity 'AGs' named entity 'AGs' named entity 'false positive' named entity 'X-rays'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software