Medical Image Segmentation and Reconstruction Based on Bayesian Level Set Method and Marching Cubes Algorithm

2011 ◽  
Vol 110-116 ◽  
pp. 4832-4836
Author(s):  
Yao Tien Chen
Keyword(s):  
Level Set Method ◽  
Surface Reconstruction ◽  
Level Set ◽  
Statistical Tests ◽  
Three Dimensional ◽  
Medical Image Segmentation ◽  
Tumor Segmentation ◽  
Marching Cubes ◽  
Appropriate Treatment ◽  
Marching Cubes Algorithm

We propose an approach, integrating Bayesian level set method with modified marching cubes algorithm for brain tissue and tumor segmentation and surface reconstruction. First, we extend the level set method based on the Bayesian risk to three-dimensional segmentation. Then, the three-dimensional Bayesian level set method is used to segment solid three-dimensional targets (e.g., tissue, whole brain, or tumor) from serial slice of medical images. Finally, the modified marching cubes algorithm is used to continuously reconstruct the surface of targets. Since each step can definitely obtain an appropriate treatment by statistical tests, the tissue and tumor segmentation and surface reconstruction are expected to be satisfied.

scholarly journals 3D Shape-Weighted Level Set Method for Breast MRI 3D Tumor Segmentation

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Chuin-Mu Wang ◽  
Chieh-Ling Huang ◽  
Sheng-Chih Yang
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
Three Dimensional ◽  
Breast Mri ◽  
Medical Image Segmentation ◽  
Tumor Segmentation ◽  
3D Segmentation ◽  
3D Shape ◽  
Segmentation Methods

Three-dimensional (3D) medical image segmentation is used to segment the target (a lesion or an organ) in 3D medical images. Through this process, 3D target information is obtained; hence, this technology is an important auxiliary tool for medical diagnosis. Although some methods have proved to be successful for two-dimensional (2D) image segmentation, their direct use in the 3D case has been unsatisfactory. To obtain more precise tumor segmentation results from 3D MR images, in this paper, we propose a method known as the 3D shape-weighted level set method (3D-SLSM). The proposed method first converts the LSM, which is superior with respect to 2D image segmentation, into a 3D algorithm that is suitable for overall calculations in 3D image models, and which improves the efficiency and accuracy of calculations. A 3D shape-weighted value is then added for each 3D-SLSM iterative process according to the changes in volume. Besides increasing the convergence rate and eliminating background noise, this shape-weighted value also brings the segmented contour closer to the actual tumor margins. To perform a quantitative analysis of 3D-SLSM and to examine its feasibility in clinical applications, we have divided our experiments into computer-simulated sequence images and actual breast MRI cases. Subsequently, we simultaneously compared various existing 3D segmentation methods. The experimental results demonstrated that 3D-SLSM exhibited precise segmentation results for both types of experimental images. In addition, 3D-SLSM showed better results for quantitative data compared with existing 3D segmentation methods.

A level set method based on domain transformation and bias correction for MRI brain tumor segmentation

2021 ◽  
Vol 352 ◽  
pp. 109091
Author(s):  
Asieh Khosravanian ◽  
Mohammad Rahmanimanesh ◽  
Parviz Keshavarzi ◽  
Saeed Mozaffari
Keyword(s):  
Brain Tumor ◽  
Level Set Method ◽  
Level Set ◽  
Bias Correction ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Mri Brain ◽  
Domain Transformation

Element-local level set method for three-dimensional dynamic crack growth

2009 ◽  
Vol 80 (12) ◽  
pp. 1520-1543 ◽  
Author(s):  
Qinglin Duan ◽  
Jeong-Hoon Song ◽  
Thomas Menouillard ◽  
Ted Belytschko
Keyword(s):  
Crack Growth ◽  
Level Set Method ◽  
Level Set ◽  
Local Level ◽  
Three Dimensional ◽  
Dynamic Crack ◽  
Dynamic Crack Growth ◽  
Local Level Set

scholarly journals Computing three-dimensional two-phase flows with a mass-conserving level set method

2008 ◽  
Vol 11 (4-6) ◽  
pp. 221-235 ◽  
Author(s):  
S. P. van der Pijl ◽  
A. Segal ◽  
C. Vuik ◽  
P. Wesseling
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Three Dimensional ◽  
Two Phase Flows ◽  
Two Phase

scholarly journals A topology optimisation for three-dimensional acoustics with the level set method and the fast multipole boundary element method

2014 ◽  
Vol 1 (4) ◽  
pp. CM0039-CM0039 ◽  
Author(s):  
Hiroshi ISAKARI ◽  
Kohei KURIYAMA ◽  
Shinya HARADA ◽  
Takayuki YAMADA ◽  
Toru TAKAHASHI ◽  
...  
Keyword(s):  
Boundary Element Method ◽  
Boundary Element ◽  
Level Set Method ◽  
Level Set ◽  
Three Dimensional ◽  
Topology Optimisation ◽  
Fast Multipole ◽  
Element Method

scholarly journals Combining interpolation and 3D level set method (I+3DLSM) for medical image segmentation

2016 ◽  
Vol 52 (8) ◽  
pp. 592-594 ◽  
Author(s):  
T. Doshi ◽  
G. Di Caterina ◽  
J. Soraghan ◽  
L. Petropoulakis ◽  
D. Grose ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
Medical Image ◽  
Medical Image Segmentation

scholarly journals Performance assessment of density and level-set topology optimisation methods for three dimensional heat sink design

2018 ◽  
Vol 12 (3) ◽  
pp. 273-287 ◽  
Author(s):  
Mani Sekaran Santhanakrishnan ◽  
Timothy Tilford ◽  
Christopher Bailey
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Heat Sink ◽  
Three Dimensional ◽  
Engineering Problem ◽  
Topology Optimisation ◽  
Design Quality ◽  
Advantages And Disadvantages ◽  
Computational Speed ◽  
Heat Sink Design

In this paper, two most prevalent topological optimisation approaches namely Density and Level set method are applied to a three dimensional heat sink design problem. The relative performance of the two approaches is compared in terms of design quality, robustness and computational speed. The work is original as for the first time it demonstrates the relative advantages and disadvantages for each method when applied to a practical engineering problem. It is additionally novel in that it presents the design of a convectively cooled heat sink by solving full thermo-fluid equations for two different solid-fluid material sets. Further, results are validated using a separate computational fluid dynamics study with the optimised designs are compared against a standard pin-fin-based heat sink design. The results show that the Density method demonstrates better performance in terms of robustness and computational speed, while Level-set method yields a better quality design in terms of final objective value.

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