Noise reduction in intravascular ultrasound images using curvelet transform and adaptive complex diffusion filter: A comparative study

2012 ◽  
Author(s):  
F. Yousefi Rizi ◽  
S. K. Setarehdan
Keyword(s):  
Comparative Study ◽  
Noise Reduction ◽  
Intravascular Ultrasound ◽  
Curvelet Transform ◽  
Ultrasound Images ◽  
Diffusion Filter ◽  
Complex Diffusion

scholarly journals Feasibility of a Novel Blood Noise Reduction Algorithm to Enhance Reproducibility of Ultra–High-Frequency Intravascular Ultrasound Images

Circulation ◽  
2000 ◽  
Vol 102 (14) ◽  
pp. 1657-1663 ◽  
Author(s):  
Kiyoshi Hibi ◽  
Atsushi Takagi ◽  
Xiangmin Zhang ◽  
Tat-Jin Teo ◽  
Heidi N. Bonneau ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Intravascular Ultrasound ◽  
High Frequency ◽  
Ultrasound Images ◽  
Reduction Algorithm ◽  
Ultra High Frequency ◽  
Noise Reduction Algorithm

Adaptive anisotropic diffusion filter for speckle noise reduction for ultrasound images

2013 ◽  
Vol 1 (1) ◽  
pp. 50 ◽  
Author(s):  
Mohammad Motiur Rahman ◽  
Mithun Kumar PK. ◽  
Abdul Aziz ◽  
Md. Gauhar Arefin ◽  
Mohammad Shorif Uddin
Keyword(s):  
Noise Reduction ◽  
Anisotropic Diffusion ◽  
Speckle Noise ◽  
Ultrasound Images ◽  
Diffusion Filter ◽  
Anisotropic Diffusion Filter ◽  
Speckle Noise Reduction

Automated Characterization of Atheromatous Plaque in Intravascular Ultrasound Images Using Neuro Fuzzy Classifier

2012 ◽  
Vol 58 (4) ◽  
pp. 425-431 ◽  
Author(s):  
D. Selvathi ◽  
N. Emimal ◽  
Henry Selvaraj
Keyword(s):  
Intravascular Ultrasound ◽  
Human Error ◽  
Human Life ◽  
Classification Performance ◽  
Atheromatous Plaque ◽  
Ultrasound Images ◽  
Fuzzy Classifier ◽  
Neuro Fuzzy ◽  
Calcified Tissues

Abstract The medical imaging field has grown significantly in recent years and demands high accuracy since it deals with human life. The idea is to reduce human error as much as possible by assisting physicians and radiologists with some automatic techniques. The use of artificial intelligent techniques has shown great potential in this field. Hence, in this paper the neuro fuzzy classifier is applied for the automated characterization of atheromatous plaque to identify the fibrotic, lipidic and calcified tissues in Intravascular Ultrasound images (IVUS) which is designed using sixteen inputs, corresponds to sixteen pixels of instantaneous scanning matrix, one output that tells whether the pixel under consideration is Fibrotic, Lipidic, Calcified or Normal pixel. The classification performance was evaluated in terms of sensitivity, specificity and accuracy and the results confirmed that the proposed system has potential in detecting the respective plaque with the average accuracy of 98.9%.

scholarly journals 950-93 Automatic Identification of Calcified Regions on Intravascular Ultrasound Images of Human Coronary Arteries Using Texture Analysis

1995 ◽  
Vol 25 (2) ◽  
pp. 180A
Author(s):  
Marco Masseroli ◽  
Robert M. Cothren ◽  
E. Murat Tuzcu ◽  
Dominique S. Meier ◽  
James D. Thomas ◽  
...  
Keyword(s):  
Texture Analysis ◽  
Intravascular Ultrasound ◽  
Coronary Arteries ◽  
Automatic Identification ◽  
Ultrasound Images
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