NDLI: Empirical greedy machine-based automatic liver segmentation in CT images

Content Provider	IET Digital Library
Author	Mourya, Gajendra Kumar Bhatia, Dinesh Handique, Akash
Abstract	Segmentation of the liver from 3D computed tomography volumes plays a significant role in trajectory development for computer-assisted interventional surgery for the liver disease. Despite a lot of studies, liver segmentation remains a challenging task due to the lack of clear edges on most liver boundaries coupled with high variability of both anatomical and intensity patterns. In addition, there is a problem with the segmentation of the left portal vein, in which the size of this vein prominently estimates the liver tumour area. The empirical greedy machine is proposed to make the precise, automated segmentation of the liver as well as the left portal vein. In which the empirical robust nature trains the features of the liver proficiently thereby segmenting the liver from other organs without the omission of adjacent organs and liver lobe region. Hence this proposed method can achieve one of the highest accuracies compared to other segmentation methods and the performance is calculated using several parameters such as volumetric overlap error, relative absolute volume difference (RVD), average symmetric absolute surface distance (ASD), root mean square surface distance, maximum symmetric ASD.
Starting Page	3333
Ending Page	3340
Page Count	8
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 14, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0690
Journal	IET Image Processing
Publisher Date	2020-04-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Segmentation Biology And Medical Computing Biomedical Imaging/measurement Computer Vision And Image Processing Technique Computerised Tomography Diseases Empirical Greedy Machine-based Automatic Liver Segmentation Feature Extraction Image Segmentation Interpolation And Function Approximation Left Portal Vein Liver Liver Disease Liver Lobe Region Liver Tumour Area Medical Image Processing Numerical Analysis Numerical Approximation And Analysis Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Precise Segmentation Radiography And Computed Tomography Segmentation Method Surfactant Tumours X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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