Multiple feature‐based portal vein classification for liver segment extraction

2021 ◽  
Author(s):  
Chan Wu ◽  
Tianyu Fu ◽  
Yuanjin Gao ◽  
Yuhan Liu ◽  
Jingfan Fan ◽  
...  
Swiss Surgery ◽  
1999 ◽  
Vol 5 (3) ◽  
pp. 143-146 ◽  
Author(s):  
Launois ◽  
Maddern ◽  
Tay

The detailed knowledge of the segmental anatomy of the liver has led to a rapid evolution in resectional surgery based on the intrahepatic distribution of the portal trinity (the hepatic artery, hepatic duct and portal vein). The classical intrafascial or extrahepatic approach is to isolate the appropriate branch of the portal vein, hepatic artery and the hepatic duct, outside the liver substance. Another method, the extrafascial approach, is to dissect the whole sheath of the pedicle directly after division of a substantial amount of the hepatic tissue to reach the pedicle, which is surrounded by a sheath, derived from Glisson's capsule. This Glissonian sheath encloses the portal trinity. In the transfissural or intrahepatic approach, these sheaths can be approached either anteriorly (after division of the main, right or umbilical fissure) or posteriorly from behind the porta hepatis. We describe the technique for approaching the Glissonian sheath and hence the hepatic pedicle structures and their branches by the intrahepatic posterior approach that allows early delineation of the liver segment without the need for ancillary techniques. In addition, the indications for the use of this technique in the technical and oncologic settings are also discussed.


2019 ◽  
Vol 39 (5) ◽  
pp. 0528004
Author(s):  
李非燕 Li Feiyan ◽  
霍宏涛 Huo Hongtao ◽  
李静 Li Jing ◽  
白杰 Bai Jie

Author(s):  
Johannes Erfurt ◽  
Wang-Q Lim ◽  
Heiko Schwarz ◽  
Detlev Marpe ◽  
Thomas Wiegand

Abstract Recent progress in video compression is seemingly reaching its limits making it very hard to improve coding efficiency significantly further. The adaptive loop filter (ALF) has been a topic of interest for many years. ALF reaches high coding gains and has motivated many researchers over the past years to further improve the state-of-the-art algorithms. The main idea of ALF is to apply a classification to partition the set of all sample locations into multiple classes. After that, Wiener filters are calculated and applied for each class. Therefore, the performance of ALF essentially relies on how its classification behaves. In this paper, we extensively analyze multiple feature-based classifications for ALF (MCALF) and extend the original MCALF by incorporating sample adaptive offset filtering. Furthermore, we derive new block-based classifications which can be applied in MCALF to reduce its complexity. Experimental results show that our extended MCALF can further improve compression efficiency compared to the original MCALF algorithm.


Author(s):  
Dr. G.G. Rajput ◽  
Anita H.B.

In a country like India where more number of scripts are in use, automatic identification of printed and handwritten script facilitates many important applications including sorting of document images and searching online archives of document images. In this paper, a multiple feature based approach is presented to identify the script type of the collection of handwritten documents. Eight popular Indian scripts are considered here. Features are extracted using Gabor filters, Discrete Cosine Transform, and Wavelets of Daubechies family. Experiments are performed to test the recognition accuracy of the proposed system at line level for bilingual scripts and later extended to trilingual scripts. We have obtained 100% recognition accuracy for bi-scripts at line level. The classification is done using k-nearest neighbour classifier.


Author(s):  
Johannes Erfurt ◽  
Wang-Q Lim ◽  
Heiko Schwarz ◽  
Detlev Marpe ◽  
Thomas Wiegand

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