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
Keyword(s):  
Pulmonary Artery ◽  
Automatic Segmentation ◽  
Graph Cuts ◽  
Surface Graph ◽  
Optimal Surface ◽  
Fully Automatic ◽  
Contrast Ct

Aorta and pulmonary artery segmentation using optimal surface graph cuts in non-contrast CT

2018 ◽  
Author(s):  
Zahra Sedghi Gamechi ◽  
Marleen de Bruijne ◽  
Andres M. Arias-Lorza ◽  
Jesper Holst Pedersen
Keyword(s):  
Pulmonary Artery ◽  
Graph Cuts ◽  
Surface Graph ◽  
Optimal Surface ◽  
Contrast Ct

scholarly journals Carotid Artery Wall Segmentation in Multispectral MRI by Coupled Optimal Surface Graph Cuts

2016 ◽  
Vol 35 (3) ◽  
pp. 901-911 ◽  
Author(s):  
Andres M. Arias-Lorza ◽  
Jens Petersen ◽  
Arna van Engelen ◽  
Mariana Selwaness ◽  
Aad van der Lugt ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Graph Cuts ◽  
Artery Wall ◽  
Carotid Artery Wall ◽  
Surface Graph ◽  
Optimal Surface ◽  
Multispectral Mri

Bubble study as a medium of contrast for computerized tomography coronary angiography. (Preprint)

2020 ◽  
Author(s):  
Vijay Shah ◽  
Justyn Huang
Keyword(s):  
Pulmonary Artery ◽  
Diagnostic Yield ◽  
Negative Contrast ◽  
Hounsfield Unit ◽  
Hounsfield Units ◽  
Computed Tomographic ◽  
Invasive Test ◽  
Clinical Difference ◽  
Contrast Ct ◽  
Scan Protocol

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

Fully automatic segmentation of sinonasal cavity and pharyngeal airway based on convolutional neural networks

2021 ◽  
Vol 159 (6) ◽  
pp. 824-835.e1
Author(s):  
Rosalia Leonardi ◽  
Antonino Lo Giudice ◽  
Marco Farronato ◽  
Vincenzo Ronsivalle ◽  
Silvia Allegrini ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Automatic Segmentation ◽  
Pharyngeal Airway ◽  
Fully Automatic

scholarly journals Automatic segmentation and classification of seven-segment display digits on auroral images

2016 ◽  
Vol 5 (2) ◽  
pp. 305-314 ◽  
Author(s):  
Tuomas Savolainen ◽  
Daniel Keith Whiter ◽  
Noora Partamies
Keyword(s):  
Automatic Segmentation ◽  
Scientific Information ◽  
Spherical Mirror ◽  
Automatic Method ◽  
Time Period ◽  
Film Images ◽  
Fully Automatic ◽  
Night Sky

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.

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