A New Morphological Approach for Removing Speckle Noise and Emphasizing Defect Features in Ultrasonic Images

Song, Young-Won; Удпа, Сатиш С.

doi:10.1007/978-1-4615-5947-4_95

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…d) Image part (4): an inward pixel is a condition that occurs when previous (B) and next estimated-pixel (C) are inside the initial contour (A), but the next estimated-pixed has a longer displacement than the previous pixel. e) Image part (5): another inward pixel is a condition that also occurs when previous pixel (B) is outside the initial contour and the next estimated-pixel (C) are inside the initial contour (A). f) Image part (6): an inward pixel is a condition that occurs when previous (B) and next estimated-pixel (C) are outside the initial contour (A), but the next estimated-pixed has a shorter displacement than the previous pixel.…”

Section: Flow Direction Determinationmentioning

confidence: 99%

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Cardiac Motions Classification on Sequential PSAX Echocardiogram

Aziz¹,

Sigit²,

Basuki³

et al. 2018

IJEECS

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<p>Cardiac wall motions classification on 2-dimensional (2D) echocardiographic images is an important issue for quantitative diagnosiing of heart disease. Unfortunately, the bad quality of echocardiogram cause computationally classification on cardiac wall motions is still become a big homework for many researchers to provide the best result. Echocardiogram is produced by soundwaves which absolutely make its images have speckle noise in different intensity. Therefore, this research improves a set of methodology to classify cardiac wall motion semi-automatically. Raw echocardiogram will be enhanced and segmented to take the boundary of endocardium of left ventricular in PSAX cardiac images. New improvement of Semi-automatically methodology is approach on detecting the contour of endocardium and will be inputed as good features in Lucas-Kanade Optical Flow in all sequential echocargraphic images. On classifying cardiac wall motions, this research proposes two important features including length of displacement and flow direction. New proprosed flow determination algorithm and Euclidean distance is used to calculate those features. All the features will be trained by Neural Network (NN) and validated by Leave One Out (LOO) to get accurate result. NN method, which is validated by LOO, has the best result of 81.82% correctness than the other compared methods.</p>

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Section: Flow Direction Determinationmentioning

confidence: 99%

“…This case motivates some of engineers start to create various inventions related to image processing on echocardiogram. Some of the inventions focus on [4][5][6][7]. The objective of enhancement is to remove speckle noise and sharpen in echocardiographic image.…”

Section: Introductionmentioning

confidence: 99%

Cardiac Motions Classification on Sequential PSAX Echocardiogram

Aziz¹,

Sigit²,

Basuki³

et al. 2018

IJEECS

View full text Add to dashboard Cite

show abstract

“…In addition they are usually computationally expensive to implement [87]. An alternative morphological approach for reducing speckle noise in ultrasonic images that uses a sequence of simple closing operations to generate residual images was proposed in [97,98], Since each residual image contains noise as well as features of interest, it is necessary to isolate the features fi"om the noise. In general, the amplitudes associated with ultrasonic speckle noise are lower than those of features.…”

Section: Literature Review: Noise Reduction Approachesmentioning

confidence: 99%

NDE data fusion using morphological approaches

Song¹

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A New Morphological Approach for Removing Speckle Noise and Emphasizing Defect Features in Ultrasonic Images

Cited by 2 publications

References 5 publications

Cardiac Motions Classification on Sequential PSAX Echocardiogram

Cardiac Motions Classification on Sequential PSAX Echocardiogram

NDE data fusion using morphological approaches

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