Biomedical Image Processing / Medical Image Processing
Bahram Momen Mehrabani; Mohammad Javad Abolhassani; Alireza Ahmadian; Javad Alirezaie
Volume 3, Issue 1 , June 2009, , Pages 47-54
Abstract
The main purpose of this work is introducing a novel method of temperature monitoring using B-Mode Ultrasound digital images. Thermal dependence of sound speed causes a virtual displacement of scatterer particles. The virtual displacement is computed using speckle tracking methods. Horn-Shunck algorithm ...
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The main purpose of this work is introducing a novel method of temperature monitoring using B-Mode Ultrasound digital images. Thermal dependence of sound speed causes a virtual displacement of scatterer particles. The virtual displacement is computed using speckle tracking methods. Horn-Shunck algorithm was applied to a tissue mimicking phantom to measure the virtual displacement. A heating resistor was used in this phantom to generate temperature elevation. The DICOM ultrasound images were acquired using commercial SIMENES ultrasound imaging system with 10MHz linear probe. The accuracy of noninvasive temperature estimation was measured comparing with invasive temperature measurement. The phantom is warmed up to the 8. The mean error of temperature estimation was found to be 0.4°C and peak error 0.9°C. Fast temperature estimation can be achieved using Optical-Flow methods. This Method is a differential based motion estimation method that estimates displacement by calculating the optical pattern changes caused by movements between two frames. Noise sensitivity is the main infirmity of Horn-Schunck method.
Biological Computer Modeling / Biological Computer Simulation
Fereshte Yousefi Rizi; Alireza Ahmadian; Javad Alirezaie; Emadoddin Fatemizadeh; Nader Rezaei
Volume 2, Issue 3 , June 2008, , Pages 165-177
Abstract
Partial volume effect and image noise greatly decrease the visibility of the airway wall. Another dilemma with airway segmentation methods, which significantly influences their accuracy, is the leakage into the extra-luminal regions due to thinness of the airway wall during the process of segmentation. ...
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Partial volume effect and image noise greatly decrease the visibility of the airway wall. Another dilemma with airway segmentation methods, which significantly influences their accuracy, is the leakage into the extra-luminal regions due to thinness of the airway wall during the process of segmentation. A solution to this problem in the previous methods was based on leak detection and reduction by adjusting the segmentation parameters and performing the whole segmentation process, which is very time consuming and demands user interaction. The new strategy presented here is to prevent the leakage by taking the advantage of the fact that the airway branches are cylindrically shaped objects. This has been achieved by introducing a new mathematical shape optimization approach embedded in FC-FCM algorithm to retain the cylindrical properties of the airway branches during the segmentation process. The main role of this optimization approach is to detect and correct the underlying voxels which belonging to the airway by satisfying both conditions of the fuzzy connectivity and shape features. The proposed FC-FCM algorithm was first applied on four data sets each containing 430 CT images of CT images of airway tree. The result showed an accuracy of 93% obtained for segmentation of the airway tree up to the fourth generation. We then applied OPT-FC-FCM algorithm to segment the airway tree with optimization process up to the sixth generation of airway. The result proves the ability of our proposed method to complete a visually acceptable segmentation of airway trees with no leakage. The number of detected branches was found 65 (4 times of those obtained by using just the FC-FCM method).
