Retrieval of 4d dual energy CT for pulmonary embolism diagnosis

Authors:
Antonio Foncubierta---Rodríguez;Alejandro Vargas;Alexandra Platon;Pierre---Alexandre Poletti;Henning Müller;Adrien Depeursinge
Affiliations:
University of Applied Sciences Western Switzerland (HES---SO), Switzerland;University Hospitals of Geneva (HUG), Switzerland;University Hospitals of Geneva (HUG), Switzerland;University Hospitals of Geneva (HUG), Switzerland;University of Applied Sciences Western Switzerland (HES---SO), Switzerland, University Hospitals of Geneva (HUG), Switzerland;University of Applied Sciences Western Switzerland (HES---SO), Switzerland, University Hospitals of Geneva (HUG), Switzerland
Venue:
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Year:
2012

Citing 5
Cited 1

Information Retrieval

Information Retrieval
Video Google: A Text Retrieval Approach to Object Matching in Videos

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Automated 3D segmentation of lung fields in thin slice CT exploiting wavelet preprocessing

CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Using multiscale visual words for lung texture classification and retrieval

MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Vessel Tree Segmentation in Presence of Interstitial Lung Disease in MDCT

IEEE Transactions on Information Technology in Biomedicine

Overview of the third workshop on medical content---based retrieval for clinical decision support (MCBR---CDS 2012)

MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pulmonary embolism is a common condition with high short---term morbidity. Pulmonary embolism can be treated successfully but diagnosis remains difficult due to the large variability of symptoms, which are often non---specific including breath shortness, chest pain and cough. Dual energy CT produces 4---dimensional data by acquiring variation of attenuation with respect to spatial coordinates and also with respect to the energy level. This additional information opens the possibility of discriminating tissue with specific material content, such as bone and adjacent contrast. Despite having already been available for clinical use for a while, there are few applications where Dual energy CT is currently showing a clear clinical advantage. In this article we propose to use the additional energy---level data in a 4D dataset to quantify texture changes in lung parenchyma as a way of finding parenchyma perfusion deficits characteristic of pulmonary embolism.