Recent Advances of Wavelet Transform and Their Applications [Working Title], 2022
Medical images are often corrupted by white noise, blurring and contrast defects. Consequently, i... more Medical images are often corrupted by white noise, blurring and contrast defects. Consequently, important medical information may be degraded or completely masked. Advanced medical diagnostics and pathological analysis utilize information obtained from medical images. Consequently, the best techniques must be applied to capture, compress, store, retrieve and share these images. Recently, the wavelet transform technique has been applied to enhance and compress medical images. This review focuses on the trends of wavelet-based medical image processing techniques. A summary of the application of wavelets to enhance and compress medical images such as magnetic resonance imaging (MRI), computerized tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), and X-ray is provided. Morphological techniques such as closing, thinning and pruning are combined with wavelets methods to extract the features from the medical images.
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2019
Medical image processing algorithms significantly affect the precision of disease diagnostic proc... more Medical image processing algorithms significantly affect the precision of disease diagnostic process. This makes it crucial to improve the quality of a medical image with the goal to enhance perceivability of the points of interest in order to obtain accurate diagnosis of a patient. Despite the reliance of various medical diagnostics on X-rays, they are usually plagued by dark and low contrast properties. Sought-after details in X-rays can only be accessed by means of digital image processing techniques, despite the fact that these techniques are far from being perfect. In this paper, we implement a wavelet decomposition and reconstruction technique to enhance radiograph properties, using a series of morphological erosion and dilation to improve the visual quality of the chest radiographs for the detection of cancer nodules.
International Journal of Computer Applications, 2017
Wavelet denoising of medical images relies on the technique of thresholding. A disadvantage of th... more Wavelet denoising of medical images relies on the technique of thresholding. A disadvantage of this method is that even though it adequately removes noise in an image, it introduces unwanted artifacts into the image near discontinuities due to Gibbs phenomenon. A total variation method for enhancing chest radiographs is implemented. The approach focuses on lung nodules detection using chest radiographs (CRs) and the method achieves high image sensitivity and could reduce the average number of false positives radiologists encounter.
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2019
Copyright c Frequency and transform domain techniques [1] such as the discrete wavelet transform ... more Copyright c Frequency and transform domain techniques [1] such as the discrete wavelet transform 2 ). The convolution operator accounted for the deblurring effect resulting from the image capturing equipment [3], usually ignored in earlier results. We implemented our algorithm in MATLAB (TM) with our method consistently producing quality results. Figure illustrates the difficulty of spotting cancer nodules in chest radiographs with the naked eye.
We consider a wavelet-based solution to the stochastic heat equation with random inputs. Computat... more We consider a wavelet-based solution to the stochastic heat equation with random inputs. Computational methods based on the wavelet transform are analyzed for solving three types of stochastic heat equation. The methods are shown to be very convenient for solving such problems, since the initial and boundary conditions are taken into account automatically. The results reveal that the wavelet algorithms are very accurate and efficient.
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Papers by Matilda Wilson