A View on despeckling in Ultrasound Imaging

2014

Ultrasound imaging is a widely used medical imaging modality. But the major issue with ultrasound images is the presence of speckle noise, which is an inherent limitation of ultrasound images. This research work focuses on speckle noise reduction in ultrasound images. Various predefined techniques for despeckling are studied thoroughly and a novel approach is proposed. In addition, comparison of predefined and proposed technique is done both on qualitative and quantitative level. Four different metrics are used for comparative study of various image filtering techniques. Keywords— Denoising Filters, Digital Image Processing, Image Enhancement, Qualitative Metrics

International Journal of Computer Applications, 2016

Ultrasound is a widely used medical imaging technique used for diagnostic purposes. But the major problem with these images is that they are inherently corrupted by speckle. The presence of speckle severely hampers the interpretation and analysis of medical ultrasonic images. In this paper, a comparison of various speckle reducing spatial and wavelet based methods has been carried out while de-speckling the image. These methods are evaluated and compared in terms of filter assessment parameters namely Peak Signal to Noise Ratio (PSNR), MSSIM (Mean Structural Similarity), FOM (Figure of Merit) and Method noise and consequently classified into three categories-outstanding, average and below average on the basis of their performance.

IOSR Journal of Electrical and Electronics Engineering, 2013

In medical image processing image denoising has become a very essential exercise all through the diagnose. Medical images are often deteriorated by noise due to a serious sources of interferences and other phenomenon that affect the measurement process in an imaging and acquisition system. Speckle noise is a random mottling of the image with bright and dark spots, which obscures fine details and degrades the delectability of low contrast lesions. Speckle noise occurrence is often undesirable since it affects the tasks of human interpretation and diagnosis. Speckle noise is a granular noise that inherently exists in and degrades the quality of the images. Generally it is found in Ultrasound image and radar image. Various noise removing methods has been introduced. This paper run a comparative study on various filter efficiencies in removing speckle noise from medical ultrasound images using statistical measures.

2013

Ultrasound imaging is used for early detection of abnormality of fetus. Speckle noise is considered as a primary source of medical ultrasound imaging noise and it must be filtered out. Several approaches are there for noise reduction. Filtering is one of the medical image processing techniques for noise reduction. In this paper a study of various filtering techniques for removal of speckle noise from ultrasound images is done. Despeckling improves the quality of the ultrasound images. Keywords—Ultrasound imaging; Speckle noise; Filtering; Despeckling.

IEEE Transactions on Instrumentation and Measurement, 2013

This paper presents a novel parametric thresholding procedure to reduce the effect of speckle noise in ultrasound (US) medical images. The method comprises the use of an adaptive data-driven exponential operator that operates on wavelet coefficients of the US image to suppress undesired effects of disturbances, preserving signal details. The obtained results demonstrate that the proposed denoising method increases the medical image quality and, therefore, it can be a useful tool in medical diagnosis. Index Terms-Scattering, speckle noise, thresholding, ultrasound medical imaging, wavelet transform. I. Introduction M EDICAL IMAGES are very useful tools to investigate the anatomy of the human body, to diagnose diseases, and to examine various illnesses. This discipline incorporates radiology, nuclear medicine, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasonography. Each of these methods ensures important performances but has different limitations. CT provides high resolution images, especially for bone structures, but exposes patients to radiation dose [1]; instead, MRI provides high quality images, especially for soft tissues, but requires long examination time [2]. Ultrasound (US) imaging has been considered, for many years, the best technique for organ and soft tissue imaging and today, it is often preferred because it is economic, portable, adaptable, non-surgical, and without ionizing radiation. US images are obtained in real time by processing the echo signals reflected by body tissues, which have different acoustic impedances. Unfortunately, ultrasonography gives low quality images, which makes their interpretation difficult as they strongly depend on the operator's skill. This limitation is mainly due to the presence of speckle noise [3]. Speckle is an undesirable interference effect occurring when two or more US waves interfere with each other, constructively or destructively, producing bright and dark spots. It reduces both spatial and contrast resolutions in US images, and contributes to a lower signal-to-noise ratio Manuscript

Speckle noise is a different kind of noise which mostly occurs in coherence imaging system like ultrasound images, lasers, sonar, synthetic aperture of radar etc. So, in ultrasound images, the presence of speckle noise results in decrement of quality of an image and due this noise it becomes difficult for human and doctors to diagnose. So it cannot be possible to interpret the change with naked eyes. It also becomes hard to differentiate between speckle noise and clinical information because speckle noise behaves like information. So it is necessary to overcome this problem by reducing noise. Many numerical methods are proposed for filtering of speckle noise or speckle suppression. This paper presents a comparative review of various speckle reduction filters. These filters have different results and behaviour. Similarly some filters do better coherence, edge enhancement and segmentation etc. In the end, it provides some commonly used filtering techniques for de-noising.

The ultrasound images, the speckle noise is inherent in medical ultrasound images and it is the cause of reduced contrast-to-noise ratio and resolution. The presence of speckle noise is not attractive because it reduces the image quality and affects the tasks of the individual interpretation and paper diagnosis. In this paper, we study various techniques to reduce speckle noise from ultrasound images Post acquisition method as the only scale spatial filtering method and multi-scale method.

Expert Systems with Applications, 2009

This article investigates and compiles some of the techniques mostly used in the smoothing or suppression of speckle noise in ultrasound images. With this information, a comparison of all the methods studied is done based on an experiment, using quality metrics to test their performance and show the benefits each one can contribute. To test the methods, a synthetic, noise-free image of a kidney is created and later simulations using Field II program to corrupt it are performed. This way, the smoothing techniques can be compared using numeric metrics, taking the noise-free image as a reference. Since real ultrasound images are already noise corrupted images and real noise-free images do not exist, conventional metrics cannot be used to indicate the quality obtained with filtering. Nevertheless, we propose the use of the tendencies observed in our study in real images.

The existences of noise in the medical images impose misleading of diagnostic processes, because of the radiation problem while acquiring images. The medical images mostly affected by the speckle noise over other natural noises. There are number of noise removal techniques for speckle noise is proposed in both spatial and frequency domain. In this paper, we propose a frequency domain method using wavelet based noise removal technique to remove speckle noise that exists in the ultrasound images. Moreover, we have implemented two different methods in terms of decomposing the images. We used Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT) for decompose the images. For comparative analysis, the performance of these filtering techniques is quantitatively evaluated through Peak Signal to Noise Ratio (PSNR). Keyword-Speckle Noise, Ultrasound Image, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT). I. INTRODUCTION In the medical imaging field, the noises occurring in the images are a crucial issue that leads to faulty decision during the patient diagnostics processes. There are variety of noise removal techniques also exists for mixed noises [1]. Noise removal techniques are constructed through spatial or frequency domain. Spatial filtering is nothing but the filtering operations that are performed directly on the intensity of the pixels [2]. It works by simply moving the kernel (i.e. filter mask) throughout the image from point to point. It mainly classified into smoothing, order-statistics and sharpening filtering. Ultrasound is one of the low cost medical imaging modality with simpler operations and so that used widely. High frequency sound waves are used to capture the inner organs [3]. The ultrasound image is produced by the reflection of the waves from the body structures. The amplitude of the signal and time taken for the wave to travel through the body are the two main factors to construct an ultrasound image. Moreover, ultrasound is a sound wave with frequencies higher than the upper audible limit of human hearing. The frequencies that operated in ultrasound devices are ranges from 20 kHz up to several gigahertz. Health care professionals uses ultrasound images to view the internal organs. During pregnancy, doctors are uses ultrasound to view the fetus, because it does not expose any radiation like other modalities. The noise occurrence in this modality is a big problem that occurs due to the value of the clear nature of the trend transferring [4]. These noises corrupt the images and often lead to incorrect diagnosis [5]. Medical imaging modalities are affected by different types of noises especially the ultrasound images are mainly affected by speckle noise. Speckle is a granular noise that exists inherently and it degrades the quality of the images such as synthetic aperture radar (SAR), medical ultrasound and optical coherence tomography images [6]. Reducing these speckle noise from a noisy image is the complicated step in medical image processing. Speckle noise degrades image quality with a backscattered wave appearance which originates from many sources like microscopic spreader reflections that pass through internal organs. It makes much difficulty for the observer to discriminate fine detail of the images while diagnostic processes. Thus, denoising or reducing these speckle noise from a noisy image has become the predominant step in medical field. Some spatial domain filtering techniques are existing for removing noises [7]. Ultimately, the speckle noise addresses the contrast related problems on images. So, there is great need to construct a denoising method to remove the speckle [8]. In this paper, we experimented the ultrasound images which are affected by speckle noise for denoising. A wavelet based image filtering technique is applied to ultrasound images which effectively remove the noises. In addition, the performance of aforementioned filters is compared (in terms of PSNR) and discussed in the following sections. This paper is further organized as follows: Section 2 contains the brief introduction about the Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT), our proposed method is explained in section 3, the results and discussion included in section 4 and we conclude our paper in section 5.

2014

Ultrasound imaging is a widely used medical imaging modality because it is safe, allows real-time visualization of moving structures, and is relatively inexpensive. But the major issue with ultrasound images is the presence of speckle noise, which is an inherent limitation of ultrasound images. Various filters are used to reduce the speckle noise and to enhance the quality of the image. This work focuses on the study of various filters used for image enhancement.