Speckle Noise Reduction for 3-D Ultrasound Images by Optimum Threshold Parameter Estimation of Wavelet Coefficients Using Fisher Discriminant Analysis
Rafid Mostafiz, Mohammad Motiur Rahman, Mithun Kumar PK, Md. Ashraful Islam · International journal of imaging and robotics · 2017
This paper introduces an approach of speckle noise reduction for 3D ultrasound images. 3D ultrasound is a popular diagnostic system in assessing the progression of diseases for its non-invasive, inexpensive and real-time nature. Speckle noise often obscures the fine details and degrades the spatial resolution and, contrast quality that makes the interpretation of ultrasound more difficult. The proposed method estimates an optimum threshold value of wavelet coefficient using Fisher Discriminant Analysis (FDA) for reducing the speckles in 3D volume of ultrasound images. FDA has applied on 2D wavelet transformation, then explored and extended to 3D. The 3D volume rendering is performed on the basis of an integration of 2D slice images that provides strong speckle reduction and edge preservation. Our experimental result is compared with the several other existing state of the art threshold methods. The observation shows that, the proposed method also gives better results, in contrast resolution and MSE.