scholarly journals Assessment of fully automatic segmentation of pulmonary artery and aorta on non‐contrast CT with optimal surface graph cuts

2021 ◽  
Author(s):  
Zahra Sedghi Gamechi ◽  
Andres M. Arias‐Lorza ◽  
Zaigham Saghir ◽  
Daniel Bos ◽  
Marleen Bruijne
Author(s):  
Zahra Sedghi Gamechi ◽  
Marleen de Bruijne ◽  
Andres M. Arias-Lorza ◽  
Jesper Holst Pedersen

2016 ◽  
Vol 35 (3) ◽  
pp. 901-911 ◽  
Author(s):  
Andres M. Arias-Lorza ◽  
Jens Petersen ◽  
Arna van Engelen ◽  
Mariana Selwaness ◽  
Aad van der Lugt ◽  
...  

2020 ◽  
Author(s):  
Vijay Shah ◽  
Justyn Huang

BACKGROUND Computed tomographic coronary angiogram (CTCA) is a non-invasive test with a negative predictive value of nearly 100% for the detection of coronary artery study. While diagnostic yield of a dedicated CTCA with bubble contrast is not yet evaluated OBJECTIVE To assess the diagnostic performance of injected bubble contrast and ability to measure difference in hounsfield units and use it as a "negative contrast" in computed tomographic METHODS This is a single center, single patient study. Baseline acquisition of a non-contrast CT scan was acquired to get hounsfield unit count in the aorta and pulmonary artery- (Calcium scan protocol) 1.4 mGy (19.5 mGy/cm). Secondly, Echo contrasts (Definity) - 5mls was injected and an echocardiogram confirmed filling in the aortic region. Finally, bubble contrast (1ml air, 8mls water and 1mls blood was drawn up and agitated through a 3 way tap) - was injected, a timing run was initiated to calculate for the bubbles to opacity the pulmonary artery. The same scan protocol was used– 1.4 mGy (19.5 mGy/cm). RESULTS Hounsfield units’ difference in the aorta and pulmonary artery from baseline compared to echo contrast and bubble contrast were not significant. CONCLUSIONS We believe this is the first ever recorded case to use bubbles as CT contrast. While results were not significant, secondary to small volume of bubbles injected. Further research needs to be implemented to assess clinical difference with amount of bubbles and volume required. CLINICALTRIAL Single centre study


2021 ◽  
Vol 159 (6) ◽  
pp. 824-835.e1
Author(s):  
Rosalia Leonardi ◽  
Antonino Lo Giudice ◽  
Marco Farronato ◽  
Vincenzo Ronsivalle ◽  
Silvia Allegrini ◽  
...  

2016 ◽  
Vol 5 (2) ◽  
pp. 305-314 ◽  
Author(s):  
Tuomas Savolainen ◽  
Daniel Keith Whiter ◽  
Noora Partamies

Abstract. In this paper we describe a new and fully automatic method for segmenting and classifying digits in seven-segment displays. The method is applied to a dataset consisting of about 7 million auroral all-sky images taken during the time period of 1973–1997 at camera stations centred around Sodankylä observatory in northern Finland. In each image there is a clock display for the date and time together with the reflection of the whole night sky through a spherical mirror. The digitised film images of the night sky contain valuable scientific information but are impractical to use without an automatic method for extracting the date–time from the display. We describe the implementation and the results of such a method in detail in this paper.


Sign in / Sign up

Export Citation Format

Share Document