scholarly journals Model-Free, Occlusion Accommodating Active Contour Tracking

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Mohamed Ben Salah ◽  
Amar Mitiche
Keyword(s):  
Active Contour ◽  
Evolution Equations ◽  
Infrared Imaging ◽  
Contour Method ◽  
Image Modeling ◽  
Model Free ◽  
Level Set Evolution ◽  
Kernel Form ◽  
Objective Functional ◽  
Active Curve

This study investigates tracking in monocular image sequences by a model-free, occlusion accommodating active contour method. The objective functional contains a model-free shape tracking term to constrain the active curve in a frame to have a shape which approximates as closely as possible the shape of the active curve in the preceding frame. It complements a kernel photometric tracking term which constrains the active curve in a frame to enclose an intensity profile that matches as closely as possible the profile within the curve in the preceding frame. This data term is in kernel form so as to forgo image modeling. The method, which is exclusively driven by the curve/level set evolution equations derived from the objective functional Euler-Lagrange conditions, can track several objects independently. Experimental validation includes examples with infrared imaging, occlusion, clutter, and articulated motion.

SEGMENTATION OF ABDOMEN DISEASES USING ACTIVE CONTOUR MODELS IN CT IMAGES

2015 ◽  
Vol 27 (05) ◽  
pp. 1550047 ◽  
Author(s):  
Gaurav Sethi ◽  
B. S. Saini
Keyword(s):  
Level Set ◽  
Active Contour ◽  
Active Contour Model ◽  
Diagnostic System ◽  
Ct Images ◽  
Active Contour Models ◽  
Segmentation Methods ◽  
Contour Models ◽  
Edge Based ◽  
Level Set Evolution

Precise segmentation of abdomen diseases like tumor, cyst and stone are crucial in the design of a computer aided diagnostic system. The complexity of shapes and similarity of texture of disease with the surrounding tissues makes the segmentation of abdomen related diseases much more challenging. Thus, this paper is devoted to the segmentation of abdomen diseases using active contour models. The active contour models are formulated using the level-set method. Edge-based Distance Regularized Level Set Evolution (DRLSE) and region based Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) are used for segmentation of various abdomen diseases. These segmentation methods are applied on 60 CT images (20 images each of tumor, cyst and stone). Comparative analysis shows that edge-based active contour models are able to segment abdomen disease more accurately than region-based level set active contour model.

scholarly journals SEGMENTASI CITRA THORAX PARU-PARU MANUSIA DARI SINAR-X MENGGUNAKAN METODE KONTUR AKTIF

2019 ◽  
Vol 4 (2) ◽  
pp. 8-10
Author(s):  
Sintha Syaputri ◽  
Zulkarnain
Keyword(s):  
Active Contour ◽  
Active Contours ◽  
Contour Method ◽  
Image Objects ◽  
Contour Segmentation ◽  
Segmentation Process ◽  
Coordinate Position ◽  
Image Improvement ◽  
The Right

Research on medical image objects in the form of lung images of thoracic X-Rayis increasingly being developed because the information contained in medical images is used to analyze and determine the shape of the lungs. The process of normalization and image improvement is needed and continued with the segmentation process using the right method. The active snake contour method is used because it is resistant to the noise around the object. The research has been usedthe Matlab software GUI program version R2015a. The image through the initial preprocessing stage is converted into a grayscale image. The segmentation process used after the initialization process in the form of a small circle curve placed of the object to be segmented and the determination position of the active contour or detemination of the active parameters of the contour. Determination of the value active contour parameters greatly influences the results of segmentation and influences the direction of active contour movement. If the active coordinate position of the contour is outside the area to be segmented it will cause active contours to move away from the object. Validation the level of accuracy of segmentation results is done by comparing the results of the snake active contour segmentation to the results of manual segmentationused MSE method

A 3D Hermite-based multiscale local active contour method with elliptical shape constraints for segmentation of cardiac MR and CT volumes

2017 ◽  
Vol 56 (5) ◽  
pp. 833-851 ◽  
Author(s):  
Leiner Barba-J ◽  
Boris Escalante-Ramírez ◽  
Enrique Vallejo Venegas ◽  
Fernando Arámbula Cosío
Keyword(s):  
Active Contour ◽  
Contour Method ◽  
Shape Constraints ◽  
Cardiac Mr ◽  
Elliptical Shape ◽  
Active Contour Method
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