scholarly journals From clamped local shape models to global shape model

2013 ◽  
Author(s):  
Hui Fang ◽  
Jingjing Deng ◽  
Xianghua Xie ◽  
Philip W. Grant
Keyword(s):  
Shape Model ◽  
Local Shape ◽  
Global Shape ◽  
Shape Models

Global precedence and response activation: Evidence from LRPs

2002 ◽  
Vol 55 (1) ◽  
pp. 289-310 ◽  
Author(s):  
Jeff Miller ◽  
David Navon
Keyword(s):  
Global Precedence ◽  
Local Shape ◽  
Global Shape ◽  
Preliminary Information ◽  
Readiness Potentials ◽  
Global Advantage ◽  
Response Activation ◽  
Lateralized Readiness Potentials

Lateralized readiness potentials (LRPs) were measured in left/right/no-go tasks using compound global/local stimuli. In Experiment 1, participants responded to local target shapes and ignored global ones. RTs were affected by the congruence of the global shape with the local one, and LRPs indicated that irrelevant global shapes activated the responses with which they were associated. In Experiment 2, participants responded to conjunctions of target shapes at both levels, withholding the response if a target appeared at only one level. Global shapes activated responses in no-go trials, but local shapes did not. The results are consistent with partial-output models in which preliminary information about global shape can partially activate responses that are inconsistent with the local shape. They also demonstrate that part of the global advantage arises early, before response activation begins and probably before recognition of the local shape.

scholarly journals KLASIFIKASI OSTEOARTHRITIS BERBASIS DUAL TREE COMPLEX WAVELET TRANSFORM DAN CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION (CLAHE) MENGGUNAKAN ACTIVE SHAPE MODELS

2020 ◽  
Vol 3 (1) ◽  
pp. 15
Author(s):  
Mohammad Meizaki Fatihin ◽  
Farid Baskoro ◽  
Arif Widodo
Keyword(s):  
Histogram Equalization ◽  
Complex Wavelet Transform ◽  
Shape Model ◽  
X Ray ◽  
Active Shape Models ◽  
Adaptive Histogram Equalization ◽  
Shape Models ◽  
Active Shape ◽  
Osteoarthritis Initiative ◽  
Grade 3

Citra adalah representasi dari informasi yang terkandung di dalamnya sehingga mata manusia dapat menganalisis dan menafsirkan informasi sesuai dengan tujuan yang diharapkan. Salah satu bentuk citra medis adalah citra x-ray. Penelitian ini mengidentifikasi gambar x-ray Osteoarthritis Lutut yang diambil pada berbagai tingkat keparahan, mulai dari KL-Grade 0 hingga KL-Grade 4. Penelitian ini menggunakan metode CLAHE dan DTCWT untuk proses preprosessing dan menggunakan metode Active Shape Model (ASM) untuk proses segmentasi, menggunakan 35 data pelatihan dan 200 data uji dari Osteoarthritis Initiative (OAI). Pengujian citra uji dalam penelitian ini dengan mengekstraksi tekstur citra menggunakan metode GLCM dan segmentasi citra menggunakan ASM, sehingga proses scanning untuk penentuan titik-titik yang berfungsi untuk mengukur ketebalan cartilage. Hasil Ekstraksi tekstur memiliki tingkat akurasi klasifikasi KL-Grade 0 57,5%, KL-Grade 1 memiliki akurasi 33.3%, KL-Grade 2 37,5%, KL-Grade 3 37,5% dan KL-Grade 4 34,3 %. Sedangkan untuk pengukuran ketebalan tulang rawan memiliki akurasi klasifikasi untuk KL-Grade 0 sebesar 62.5%, kemudian KL-Grade 1 sebesar 44.4 %, sedangkan untuk KL-Grade 2 memiliki keberhasilan klasifikasi 60%, kemudian KL-Grade 3 memiliki klasifikasi berhasil dengan benar 70%, dan untuk KL-Grade 4 51.4%.

scholarly journals Creating a 2D Active Shape Model Using itk::ImagePCAShapeModelEstimator

2011 ◽  
Author(s):  
John Durkin ◽  
David Miller ◽  
Kenneth Urish
Keyword(s):  
Active Contour ◽  
Active Shape Model ◽  
Knee Cartilage ◽  
Shape Model ◽  
Active Shape Models ◽  
Contour Segmentation ◽  
Shape Models ◽  
Segmentation Algorithms ◽  
Active Shape ◽  
Weak Boundaries

Although many variations of active contour segmentation algorithms exist, most are based on solely edge criteria and breakdown or leak at weak boundaries. One solution to this problem is constraining the segmented area to only statistically possible shapes with the guidance of a shape model. The purpose of this document is to fill the void in the ITK user guide on building active shape models. We describe how to create a 2d active shape model of articular femoral knee cartilage using ITK’s ImagePCAShapeModelEstimator. Sample code and example images are provided for displaying the initial principle components of variation. Shape models built with our code can be used for segmentation with itk::GeodesicActiveContourShapePriorLevelSetImageFilter.

Human Body Segmentation Based on Shape Model and Level Set

2013 ◽  
Vol 433-435 ◽  
pp. 261-266
Author(s):  
Ying Na Deng ◽  
Xue Mei Hou
Keyword(s):  
Level Set ◽  
Human Body ◽  
Initial Contour ◽  
Model Matching ◽  
Shape Model ◽  
Shape Models ◽  
Human Object ◽  
Body Segmentation ◽  
Human Body Segmentation ◽  
Tracking And Recognition

Human body segmentation is important for object tracking and recognition. When there are multiple human bodies, because of inter-occlusion, human body precise segmentation is difficult. A segmentation method based on prior shape model and level set is proposed. Human coarse shape models are constructed with position, scale and posture. For each human body, its corresponding human shape model is obtained by model matching by which position is obtained roughly after model matching, and object precise contour is obtained through curve evolution by multiphase level set with initial contour obtained from shape model. The proposed method could segment human object precisely.

Combining Local and Global Shape Models for Deformable Object Matching

2009 ◽  
Author(s):  
Philip A Tresadern ◽  
Harish Bhaskar ◽  
Steve A Adeshina ◽  
Chris J Taylor ◽  
Tim F Cootes
Keyword(s):  
Object Matching ◽  
Global Shape ◽  
Deformable Object ◽  
Shape Models

scholarly journals THE LOCAL SHAPE OF THE UNIVERSE IN THE INFLATIONARY LIMIT

2005 ◽  
Vol 20 (11) ◽  
pp. 2415-2420 ◽  
Author(s):  
B. MOTA ◽  
M. J. REBOUÇAS ◽  
R. TAVAKOL
Keyword(s):  
High Precision ◽  
Strong Evidence ◽  
Precision Data ◽  
Local Shape ◽  
Global Shape ◽  
High Precision Data ◽  
Topology Of The Universe ◽  
The Universe

Recent high precision data by WMAP and SDSS have provided strong evidence to suggest that the universe is nearly flat. They are also making it possible to probe the topology of the universe. Motivated by these results, we have recently studied the consequences of taking the inflationary limit, i.e. |Ω0 - 1| ≪ 0. We have shown that in this limit a generic detectable spherical or hyperbolic topology is locally indistinguishable from either [Formula: see text] or [Formula: see text], irrespective of its global shape. Here we briefly present these results and further discuss their observational implications.

New Ganymede control point network and global shape model

2015 ◽  
Vol 117 ◽  
pp. 246-249 ◽  
Author(s):  
A. Zubarev ◽  
I. Nadezhdina ◽  
J. Oberst ◽  
H. Hussmann ◽  
A. Stark
Keyword(s):  
Control Point ◽  
Shape Model ◽  
Global Shape

scholarly journals A GLOBAL SHAPE MODEL FOR SATURN’S MOON ENCELADUS FROM A DENSE PHOTOGRAMMETRIC CONTROL NETWORK

2020 ◽  
Vol V-3-2020 ◽  
pp. 579-586
Author(s):  
M. T. Bland ◽  
L. A. Weller ◽  
D. P. Mayer ◽  
B. A. Archinal
Keyword(s):  
Spatial Data ◽  
Global Ocean ◽  
Control Network ◽  
Triaxial Ellipsoid ◽  
Absolute Deviation ◽  
Data Set ◽  
Shape Model ◽  
Global Models ◽  
Global Shape ◽  
Data Infrastructure

Abstract. A planetary body’s global shape provides both insight into its geologic evolution, and a key element of any Planetary Spatial Data Infrastructure (PSDI). NASA’s Cassini mission to Saturn acquired more than 600 moderate- to high-resolution images (<500 m/pixel) of the small, geologically active moon Enceladus. The moon’s internal global ocean and intriguing geology mark it as a candidate for future exploration and motivates the development of a PSDI. Recently, two PSDI foundational data sets were created: geodetic control and orthoimages. To provide the third foundational data set, we generate a new shape model for Enceladus from Cassini images and a dense photogrammetric control network (nearly 1 million tie points) using the U.S. Geological Survey’s Integrated Software for Imagers and Spectrometers (ISIS) and the Ames Stereo Pipeline (ASP). The new shape model is near-global in extent and gridded to 2.2 km/pixel, ∼50 times better resolution than previous global models. Our calculated triaxial shape, rotation rate, and pole orientation for Enceladus is consistent with current International Astronomical Union (IAU) values to within the error; however, we determined a new prime meridian offset (Wo) of 7.063°. We calculate Enceladus’ long-wavelength topography by subtracting the best-fit triaxial ellipsoid from our shape model. The result is comparable to previous global models but can resolve topographic features as small as 5–7 km across in certain areas. To evaluate the spatially varying quality of the model, we calculate the point density (variable from 5 to more than 50 points per pixel), normalized median absolute deviation of the points within each pixel (typically less than 100 m), and the minimum expected vertical precision of each point (ranging from 29 m to 2 km).

Sign in / Sign up

Export Citation Format

Share Document