A Novel Combined Level Set Model for Carpus Segmentation from Magnetic Resonance Images with Prior Knowledge aligned in Polar Coordinate System

2021 ◽  
pp. 106245
Author(s):  
Jianzhang Li ◽  
Sven Nebelung ◽  
Justus Schock ◽  
Björn Rath ◽  
Markus Tingart ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Coordinate System ◽  
Prior Knowledge ◽  
Level Set ◽  
Magnetic Resonance Images ◽  
Polar Coordinate System ◽  
Polar Coordinate ◽  
Level Set Model

scholarly journals Sex differences of human corpus callosum revealed by polar coordinate system: magnetic resonance imaging study

2015 ◽  
Vol 74 (4) ◽  
pp. 414-420 ◽  
Author(s):  
G. Spasojević ◽  
S. Malobabić ◽  
D. Mikić ◽  
S. Vujnović ◽  
O. Pilipović Spasojević ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Sex Differences ◽  
Magnetic Resonance ◽  
Corpus Callosum ◽  
Coordinate System ◽  
Imaging Study ◽  
Polar Coordinate System ◽  
Magnetic Resonance Imaging Study ◽  
Resonance Imaging ◽  
Polar Coordinate

scholarly journals A novel combined level set model for automatic MR image segmentation

2020 ◽  
Vol 6 (3) ◽  
pp. 20-23
Author(s):  
Jianzhang Li ◽  
Sven Nebelung ◽  
Björn Rath ◽  
Markus Tingart ◽  
Jörg Eschweiler
Keyword(s):  
Magnetic Resonance ◽  
Level Set Method ◽  
Level Set ◽  
Object Segmentation ◽  
Magnetic Resonance Images ◽  
Local Region ◽  
Dice Similarity Coefficient ◽  
Edge Detector ◽  
Level Set Model

AbstractMedical image processing comes along with object segmentation, which is one of the most important tasks in that field. Nevertheless, noise and intensity inhomogeneity in magnetic resonance images challenge the segmentation procedure. The level set method has been widely used in object detection. The flexible integration of energy terms affords the level set method to deal with variable difficulties. In this paper, we introduce a novel combined level set model that mainly cooperates with an edge detector and a local region intensity descriptor. The noise and intensity inhomogeneities are eliminated by the local region intensity descriptor. The edge detector helps the level set model to locate the object boundaries more precisely. The proposed model was validated on synthesized images and magnetic resonance images of in vivo wrist bones. Comparing with the ground truth, the proposed method reached a Dice similarity coefficient of > 0.99 on all image tests, while the compared segmentation approaches failed the segmentations. The presented combined level set model can be used for the object segmentation in magnetic resonance images.

Natural Frequencies and Mode Shapes of Elliptic Plates With Boundary Characteristic Orthogonal Polynomials As Assumed Shape Functions

1991 ◽  
Author(s):  
C. Rajalingham ◽  
R. B. Bhat ◽  
G. D. Xistris
Keyword(s):  
Coordinate System ◽  
Orthogonal Polynomials ◽  
Natural Frequencies ◽  
Ritz Method ◽  
Mode Shapes ◽  
Polar Coordinate System ◽  
Free Boundaries ◽  
Natural Modes ◽  
Polar Coordinate ◽  
Boundary Characteristic

Abstract The natural frequencies and natural modes of vibration of uniform elliptic plates with clamped, simply supported and free boundaries are investigated using Rayleigh-Ritz method. A modified polar coordinate system is used to investigate the problem. Energy expressions in Cartesian coordinate system are transformed into the modified polar coordinate system. Boundary characteristic orthogonal polynomials in the radial direction, and trigonometric functions in the angular direction are used to express the deflection of the plate. These deflection shapes are classified into four basic categories, depending on its symmetrical or antisymmetrical property about the major and minor axes of the ellipse. The first six natural modes in each of the above categories are presented in the form of contour plots.

scholarly journals Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data

2016 ◽  
Vol 33 (4) ◽  
pp. 697-712 ◽  
Author(s):  
R. Andrew Weekley ◽  
R. Kent Goodrich ◽  
Larry B. Cornman
Keyword(s):  
Coordinate System ◽  
Original Data ◽  
Detection Algorithm ◽  
Polar Coordinate System ◽  
Lidar Data ◽  
Image Processing Algorithm ◽  
Polar Coordinate ◽  
Scanning Lidar ◽  
Performance Statistics ◽  
Background Fields

AbstractAn image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.

Sign in / Sign up

Export Citation Format

Share Document