Papers by Kalaivani S
A contemporary method for speckle reduction through LPSRAD is proposed for synthetic aperture rad... more A contemporary method for speckle reduction through LPSRAD is proposed for synthetic aperture radar imagery. By this method, the speckle is removed in three steps. First, the image is transformed into Gaussian and laplacian pyramid domain representation. Second, the pixels are manipulated by speckle reducing anisotropic diffusion (SRAD) and finally the processed copies are reconstructing to retrieve the resultant image. The proposed method has reduced the speckle and also the texture of structured region, edges and land surfaces are well preserved. The performance of the proposed method has been quantitatively justified through standard quality measures like mean square error (MSE), peak signal to noise ratio (PSNR) and structured similarity index (SSIM).
A signal dependent noise called speckle is an
inherent property of medical ultrasound (US) imagin... more A signal dependent noise called speckle is an
inherent property of medical ultrasound (US) imaging modality,
satellite aperture radar imaging (SAR) and optical coherence
tomography (OCT) imaging. This speckle is multiplicative in
nature and degrades the resolution, speed and accuracy of all the
post processing tasks on the US/SAR/OCT imaging modalities. In
this paper, a novel method has been proposed to reduce the
speckle by applying a new combinational PDE which exhibits the
properties of both second and fourth order partial differential
equations (PDEs). The new PDE is applied in Laplacian pyramid
domain to achieve better speckle reduction with edge
preservation and feature enhancement.
International Journal on Signal processing, Image processing and Pattern recognition, Sep 2009
Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive... more Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost and capability of forming real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. The speckle pattern depends on the structure of the image tissue and various
imaging parameters. There are two main purposes for speckle reduction in medical ultrasound imaging (1) to improve the human interpretation of ultrasound images (2) despeckling is the
preprocessing step for many ultrasound image processing tasks such as segmentation and registration. A number of methods have been proposed for speckle reduction in ultrasound imaging. While incorporating speckle reduction techniques as an aid for visual diagnosis, it has to keep in mind that certain speckle contains diagnostic information and should be retained. The objective of this paper is to give an overview about types of speckle reduction techniques in ultrasound imaging.
ACEEE International Journal on Communication, Jun 2011
This paper presents an approach for reducing speckle in ultrasound images using Coupled Partial D... more This paper presents an approach for reducing speckle in ultrasound images using Coupled Partial Differential Equation (CPDE) which has been obtained by uniting secondorder
and the fourth-order partial differential equations. Using
PDE to reduce the speckle is the noise-smoothing methods
which is getting attention widely, because PDE can keep the
edge well when it reduces the noise. We also introduced a
median regulator to guide energy source to boost the features
in the image and regularize the diffusion. The proposed
method is tested in both simulated and real medical ultrasound images. The proposed method is compared with SRAD, Perona Malik diffusion and Non linear coherent diffusion methods, our method gives better result in terms of CNR, SSIM and FOM.
International Journal on Computer Technology and Applications, Apr 2011
Ultrasonography is a powerful technique for imaging the internal anatomy with its nature of low c... more Ultrasonography is a powerful technique for imaging the internal anatomy with its nature of low cost, portability, non invasive and real time imaging formation compared with other imaging modalities. Speckle noise is an inherent nature of ultrasound images, which may have negative effect on image interpretation and diagnostic tasks. It is necessary to preprocess imagery to reduce granular, texture like noise called speckle. This preprocessing is difficult when it is needed to preserve delicate image details that are buried in speckle. In this paper we present an effective approach for speckle reduction in medical diagnostic ultrasound images. This method utilizes non linear coherent diffusion model with median regularization term as boosting source for the point and linear features in image being processed. Windowed second moment tensor is used as a diffusion tensor to estimate the local coherence. Experiments have been performed on synthetic image, simulated phantom and
clinical ultrasound images. The results are compared with existing state of art methods and our proposed method
gives comparatively better result in term of FOM, SSIM and EPI.
International Journal of Information and Electronics Engineering, Nov 2012
In this work, a compound PDE approach is proposed in multiscale for speckle reduction of diagnost... more In this work, a compound PDE approach is proposed in multiscale for speckle reduction of diagnostic Ultrasound (US) images, Satellite aperture radar (SAR) images and optical coherence tomography (OCT) images. In denoising process, it is always difficult to preserve discontinuities in one part of the image and simultaneously recovery of smooth areas in other part of image. Hence, combining different algorithms is the only way to improve the image restoration capability. In this paper, coupled PDE, complex diffusion and second order non linear diffusion are applied to layers 1, 2 and 3 of Laplacian pyramid respectively. . In each pyramid layer, using robust median estimator, gradient threshold is estimated automatically. To limit the number of iterations, mean absolute error (MAE) between two adjacent diffusion steps is used as stopping criteria. Quantitative results on synthetic data and simulated phantom show the performance of the proposed method over state of the art methods. Results on real images demonstrate that the proposed method effectively suppresses the speckle and preserves edges & structural details of the image.
A Springer Open Access journal,, Jul 18, 2012
This article proposes a technique for speckle reduction in medical ultrasound (US) imaging which ... more This article proposes a technique for speckle reduction in medical ultrasound (US) imaging which preserves the point and linear features with the added advantage of energy condensation regulator. Whatever be the post processing task in US image, the image should undergo a preprocessing step called despeckling. Nowadays, though the US machines are available with built-in speckle reduction facility, they are suffered by many practical
limitations such as limited dynamic range of the display, limited number of unique directions that an US beam scan follow to average an image and limited size of transducer, etc. The
proposed diffusion model can be used as a visual enhancement tool for interpretation as well as a preprocessing task for further diagnosis. This method incorporates two terms: diffusion and regulator. The anisotropic diffusion preserves and enhances edges and local details. The regularization enables the correction of feature broadening distortion which is the common problem in second-order diffusion-based methods. In this scheme, the diffusion matrix is designed using local coordinate transformation and the feature broadening correction term is derived from energy function. Performance of the proposed method has been illustrated using synthetic and real US data. Experiments indicate better speckle reduction and effective preservation of edges and local details.
Journal of Imaging Science and Technology, Feb 10, 2012
It has been estimated that one out of every four medical
diagnosis in the world involves ultraso... more It has been estimated that one out of every four medical
diagnosis in the world involves ultrasound imaging modality because of its noninvasive nature, low cost and capability of forming real time imaging. Ultrasonic imaging extends its application to many fields of medical diagnosis, but the utilization is being unfortunately affected by speckle noise. In this article, an efficient multiscale approach is proposed to reduce speckle, to enhance the edge information and to preserve point and linear features, rather than just inhibiting smoothing. With this approach, the image enhancement is made in three steps: First the image is transformed into Laplacian pyramid domain representation. Second, the pyramid coefficients are
manipulated by permutated diffusion, and finally the image is reconstructed from the diffused Laplacian pyramid. New permutated diffusion is proposed for coefficient manipulation for effective speckle reduction and enhancement. The proposed permutated diffusion avoids the blocky effects caused by second-order partial differential equation (PDE) and requires only little iteration compared to fourth-order PDE to converge. In each pyramid layer, a gradient threshold is estimated automatically using robust median estimator. The mean absolute error between two adjacent diffusion steps is used as a stopping criterion. Performance of the proposed approach is compared with the state of the art pyramid based methods. Experiments on synthetic data, simulated phantom and real ultrasound data set indicate effective suppression of speckle, preservation of edge information and their structural details .
Conference Presentations by Kalaivani S
Ultrasonic Speckle Reduction and Feature Enhancement Using Effective Anisotropic Diffusion
Despeckling of ultrasound imaging using median regularized coupled PDE
Despeckling of medical diagnostic Ultrasound images via Lapalcian based mixed PDE
Coupled PDE in pyramid domain for despeckling of B-Scan images
Multiscale compound PDE approach for despeckling of US/SAR/OCT images
"In this work, a compound PDE approach is
proposed in multiscale for speckle reduction of diagno... more "In this work, a compound PDE approach is
proposed in multiscale for speckle reduction of diagnostic
Ultrasound (US) images, Satellite aperture radar (SAR) images
and optical coherence tomography (OCT) images. In denoising
process, it is always difficult to preserve discontinuities in one
part of the image and simultaneously recovery of smooth areas
in other part of image. Hence, combining different algorithms is
the only way to improve the image restoration capability. In
this paper, coupled PDE, complex diffusion and second order
non linear diffusion are applied to layers 1, 2 and 3 of Laplacian
pyramid respectively. . In each pyramid layer, using robust
median estimator, gradient threshold is estimated automatically.
To limit the number of iterations, mean absolute error (MAE)
between two adjacent diffusion steps is used as stopping criteria.
Quantitative results on synthetic data and simulated phantom
show the performance of the proposed method over state of the
art methods. Results on real images demonstrate that the
proposed method effectively suppresses the speckle and
preserves edges & structural details of the image"
Talks by Kalaivani S
Matrix Anisotropic Diffusion for Ultrasonic Speckle Reduction
A View on despeckling in Ultrasound Imaging
Ultrasonic speckle reduction via flux diffusion
Laplacian Pyramid Based Despeckling in Ultrasound Imaging
A system on chip platform to integrate lifting scheme based medical image Fusion
A multi resolution approach for speckle reduction in medical diagnostic ultrasound images
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Papers by Kalaivani S
inherent property of medical ultrasound (US) imaging modality,
satellite aperture radar imaging (SAR) and optical coherence
tomography (OCT) imaging. This speckle is multiplicative in
nature and degrades the resolution, speed and accuracy of all the
post processing tasks on the US/SAR/OCT imaging modalities. In
this paper, a novel method has been proposed to reduce the
speckle by applying a new combinational PDE which exhibits the
properties of both second and fourth order partial differential
equations (PDEs). The new PDE is applied in Laplacian pyramid
domain to achieve better speckle reduction with edge
preservation and feature enhancement.
imaging parameters. There are two main purposes for speckle reduction in medical ultrasound imaging (1) to improve the human interpretation of ultrasound images (2) despeckling is the
preprocessing step for many ultrasound image processing tasks such as segmentation and registration. A number of methods have been proposed for speckle reduction in ultrasound imaging. While incorporating speckle reduction techniques as an aid for visual diagnosis, it has to keep in mind that certain speckle contains diagnostic information and should be retained. The objective of this paper is to give an overview about types of speckle reduction techniques in ultrasound imaging.
and the fourth-order partial differential equations. Using
PDE to reduce the speckle is the noise-smoothing methods
which is getting attention widely, because PDE can keep the
edge well when it reduces the noise. We also introduced a
median regulator to guide energy source to boost the features
in the image and regularize the diffusion. The proposed
method is tested in both simulated and real medical ultrasound images. The proposed method is compared with SRAD, Perona Malik diffusion and Non linear coherent diffusion methods, our method gives better result in terms of CNR, SSIM and FOM.
clinical ultrasound images. The results are compared with existing state of art methods and our proposed method
gives comparatively better result in term of FOM, SSIM and EPI.
limitations such as limited dynamic range of the display, limited number of unique directions that an US beam scan follow to average an image and limited size of transducer, etc. The
proposed diffusion model can be used as a visual enhancement tool for interpretation as well as a preprocessing task for further diagnosis. This method incorporates two terms: diffusion and regulator. The anisotropic diffusion preserves and enhances edges and local details. The regularization enables the correction of feature broadening distortion which is the common problem in second-order diffusion-based methods. In this scheme, the diffusion matrix is designed using local coordinate transformation and the feature broadening correction term is derived from energy function. Performance of the proposed method has been illustrated using synthetic and real US data. Experiments indicate better speckle reduction and effective preservation of edges and local details.
diagnosis in the world involves ultrasound imaging modality because of its noninvasive nature, low cost and capability of forming real time imaging. Ultrasonic imaging extends its application to many fields of medical diagnosis, but the utilization is being unfortunately affected by speckle noise. In this article, an efficient multiscale approach is proposed to reduce speckle, to enhance the edge information and to preserve point and linear features, rather than just inhibiting smoothing. With this approach, the image enhancement is made in three steps: First the image is transformed into Laplacian pyramid domain representation. Second, the pyramid coefficients are
manipulated by permutated diffusion, and finally the image is reconstructed from the diffused Laplacian pyramid. New permutated diffusion is proposed for coefficient manipulation for effective speckle reduction and enhancement. The proposed permutated diffusion avoids the blocky effects caused by second-order partial differential equation (PDE) and requires only little iteration compared to fourth-order PDE to converge. In each pyramid layer, a gradient threshold is estimated automatically using robust median estimator. The mean absolute error between two adjacent diffusion steps is used as a stopping criterion. Performance of the proposed approach is compared with the state of the art pyramid based methods. Experiments on synthetic data, simulated phantom and real ultrasound data set indicate effective suppression of speckle, preservation of edge information and their structural details .
Conference Presentations by Kalaivani S
proposed in multiscale for speckle reduction of diagnostic
Ultrasound (US) images, Satellite aperture radar (SAR) images
and optical coherence tomography (OCT) images. In denoising
process, it is always difficult to preserve discontinuities in one
part of the image and simultaneously recovery of smooth areas
in other part of image. Hence, combining different algorithms is
the only way to improve the image restoration capability. In
this paper, coupled PDE, complex diffusion and second order
non linear diffusion are applied to layers 1, 2 and 3 of Laplacian
pyramid respectively. . In each pyramid layer, using robust
median estimator, gradient threshold is estimated automatically.
To limit the number of iterations, mean absolute error (MAE)
between two adjacent diffusion steps is used as stopping criteria.
Quantitative results on synthetic data and simulated phantom
show the performance of the proposed method over state of the
art methods. Results on real images demonstrate that the
proposed method effectively suppresses the speckle and
preserves edges & structural details of the image"
Talks by Kalaivani S