A Hybrid Technique of Noise Reduction with Periductal Fibrosis Ultrasound Images for Periductal Fibrosis Detection System of Cholangiocarcinoma Surveillance

2014 ◽  
Vol 931-932 ◽  
pp. 1407-1411 ◽  
Author(s):  
Pichet Wayalun ◽  
Saiyan Saiyod ◽  
Nittaya Chamadol

The Cholangiocarcinoma (CCA) is a serious public health problem. The Periductal fibrosis (PDF) ultrasound images are applied for CCA surveillance because it is no side effect of radiation with patients, easy to portability and low cost. In contrast, the common problem of ultrasound images are speckle noise in which decreases the PDF detection performance. In this paper proposes a hybrid noise reduction method in the PDF detection system. The proposed noise reduction method by applying the Median filter and Fast Fourier transform based on PDF ultrasound images. The experimental results give the best performance for PDF detection system. A success rate of proposed method achieved at 70.89%.

2020 ◽  
Vol 8 (5) ◽  
pp. 1851-1854

In medical images, medical images are corrupted by different types of noise. It is important to get a precise picture and accurately observe the correspondence. Removing noise from medical images has become a very difficult problem in the field of the medical image. The most well-known noise reduction method, which is usually based on the local statistics of medical images, is efficient because of the noise reduction of medical images. In paper, an efficient and simple method for noise reduction from medical images is presented. The paper proposes a filtering system to combine both the Median filter and Gaussian filter to remove the Speckle noise form Medical and Ultrasound images. The image quality is measured through statistical quantities: Peak signal to noise ratio (PSNR). Experimental results show that the proposed system removes Speckle noise from medical images.


Author(s):  
Awais Nazir ◽  
Muhammad Shahzad Younis ◽  
Muhammad Khurram Shahzad

Speckle noise is one of the most difficult noises to remove especially in medical applications. It is a nuisance in ultrasound imaging systems which is used in about half of all medical screening systems. Thus, noise removal is an important step in these systems, thereby creating reliable, automated, and potentially low cost systems. Herein, a generalized approach MFNR (Multi-Frame Noise Removal) is used, which is a complete Noise Removal system using KDE (Kernal Density Estimation). Any given type of noise can be removed if its probability density function (PDF) is known. Herein, we extracted the PDF parameters using KDE. Noise removal and detail preservation are not contrary to each other as the case in single-frame noise removal methods. Our results showed practically complete noise removal using MFNR algorithm compared to standard noise removal tools. The Peak Signal to Noise Ratio (PSNR) performance was used as a comparison metric. This paper is an extension to our previous paper where MFNR Algorithm was showed as a general purpose complete noise removal tool for all types of noises


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 15983-15999 ◽  
Author(s):  
Carlos A. Duarte-Salazar ◽  
Andres Eduardo Castro-Ospina ◽  
Miguel A. Becerra ◽  
Edilson Delgado-Trejos

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