Automatic classification of liver veins in ultrasound images

Author(s):  
Ayce Mentese ◽  
Hasan Sakir Bilge
2019 ◽  
Vol 54 (S1) ◽  
pp. 86-87
Author(s):  
X.P. Burgos‐Artizuu ◽  
E. Eixarch ◽  
D. Coronado‐Gutierrez ◽  
B. Valenzuela ◽  
E. Bonet‐Carne ◽  
...  

2021 ◽  
Author(s):  
Iman Taghavi ◽  
Sofie Bech Andersen ◽  
Stinne Byrholdt Sogaard ◽  
Michael Bachmann Nielsen ◽  
Charlotte Mehlin Sorensen ◽  
...  

2020 ◽  
Vol 56 (S1) ◽  
pp. 162-162
Author(s):  
D. Coronado‐Gutierrez ◽  
X.P. Burgos‐Artizuu ◽  
E. Monterde ◽  
E. Eixarch ◽  
B. Valenzuela ◽  
...  

Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).


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