Abstract—Brain tumor, is one of the major causes for the increase in mortality among children and... more Abstract—Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor.
Brain tumor, is one of the major causes for the increase in mortality among children and adults. ... more Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor. In this paper, a wavelet based image fusion algorithm is applied on the Magnetic Resonance (MR) images and Computed Tomography (CT) images which are used as primary sources to extract the redundant and complementary information in order to enhance the tumor detection in the resultant fused image. The main features taken into account for detection of brain tumor are location of tumor and size of the tumor, which is further optimized through fusion of images using various wavelet transforms parameters. We discuss and enforce the principle of evaluating and comparing the performance of the algorithm applied to the images with respect to various wavelets type used for the wavelet analysis. The performance efficiency of the algorithm is evaluated on the basis of PSNR values. The obtained results are compared on the basis of PSNR with gradient vector field and big bang optimization. The algorithms are analyzed in terms of performance with respect to accuracy in estimation of tumor region and computational efficiency of the algorithms.
Brain tumor, is one of the major causes for the increase in mortality among children and adults. ... more Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor. In this paper, a wavelet based image fusion algorithm is applied on the Magnetic Resonance (MR) images and Computed Tomography (CT) images which are used as primary sources to extract the redundant and complementary information in order to enhance the tumor detection in the resultant fused image. The main features taken into account for detection of brain tumor are location of tumor and size of the tumor, which is further optimized through fusion of images using various wavelet transforms parameters. We discuss and enforce the principle of evaluating and comparing the performance of the algorithm applied to the images with respect to various wavelets type used for the wavelet analysis. The performance efficiency of the algorithm is evaluated on the basis of PSNR values. The obtained results are compared on the basis of PSNR with gradient vector field and big bang optimization. The algorithms are analyzed in terms of performance with respect to accuracy in estimation of tumor region and computational efficiency of the algorithms.
Accurate detection of size and location of brain tumor plays a vital role in the diagnosis of tum... more Accurate detection of size and location of brain tumor plays a vital role in the diagnosis of tumor. In this paper, we propose an efficient wavelet based algorithm for tumor detection which utilizes the complementary and redundant information from the Computed Tomography (CT) image and Magnetic Resonance Imaging (MRI) images. Hence this algorithm effectively uses the information provided by the CT image and MRI images there by providing a resultant fused image which increases the efficiency of tumor detection. We also evaluate the effectiveness of proposed algorithm on varying the wavelet fusion parameters like number of decompositions, type of wavelet used for the decomposition. The experimental results of the simulation on MRI and CT images show the performance efficiency of the proposed approach.
The theoretical tools of optical transformation and conformal mapping have enabled the transferen... more The theoretical tools of optical transformation and conformal mapping have enabled the transference of the concept of invisibility from the realms of mythology to scientific reality. A number of attempts have been made to achieve invisibility which relied on Nano or micro fabricated artificial composite material with spatially varying electro-magnetic properties. This approach limits the size of the invisibility region to a few wavelengths and is also very costly. Here, we experimentally solve this problem by designing a structure with low cost materials and simple manufacturing techniques based on the principles of refraction and lateral shift. This cloak developed is able to conceal macroscopic object of sizes of at least 3 orders of magnitude larger than the wavelength of light in all three dimensions. This clock can find huge application in defense and transformation optics.
Abstract—Brain tumor, is one of the major causes for the increase in mortality among children and... more Abstract—Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor.
Brain tumor, is one of the major causes for the increase in mortality among children and adults. ... more Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor. In this paper, a wavelet based image fusion algorithm is applied on the Magnetic Resonance (MR) images and Computed Tomography (CT) images which are used as primary sources to extract the redundant and complementary information in order to enhance the tumor detection in the resultant fused image. The main features taken into account for detection of brain tumor are location of tumor and size of the tumor, which is further optimized through fusion of images using various wavelet transforms parameters. We discuss and enforce the principle of evaluating and comparing the performance of the algorithm applied to the images with respect to various wavelets type used for the wavelet analysis. The performance efficiency of the algorithm is evaluated on the basis of PSNR values. The obtained results are compared on the basis of PSNR with gradient vector field and big bang optimization. The algorithms are analyzed in terms of performance with respect to accuracy in estimation of tumor region and computational efficiency of the algorithms.
Brain tumor, is one of the major causes for the increase in mortality among children and adults. ... more Brain tumor, is one of the major causes for the increase in mortality among children and adults. Detecting the regions of brain is the major challenge in tumor detection. In the field of medical image processing, multi sensor images are widely being used as potential sources to detect brain tumor. In this paper, a wavelet based image fusion algorithm is applied on the Magnetic Resonance (MR) images and Computed Tomography (CT) images which are used as primary sources to extract the redundant and complementary information in order to enhance the tumor detection in the resultant fused image. The main features taken into account for detection of brain tumor are location of tumor and size of the tumor, which is further optimized through fusion of images using various wavelet transforms parameters. We discuss and enforce the principle of evaluating and comparing the performance of the algorithm applied to the images with respect to various wavelets type used for the wavelet analysis. The performance efficiency of the algorithm is evaluated on the basis of PSNR values. The obtained results are compared on the basis of PSNR with gradient vector field and big bang optimization. The algorithms are analyzed in terms of performance with respect to accuracy in estimation of tumor region and computational efficiency of the algorithms.
Accurate detection of size and location of brain tumor plays a vital role in the diagnosis of tum... more Accurate detection of size and location of brain tumor plays a vital role in the diagnosis of tumor. In this paper, we propose an efficient wavelet based algorithm for tumor detection which utilizes the complementary and redundant information from the Computed Tomography (CT) image and Magnetic Resonance Imaging (MRI) images. Hence this algorithm effectively uses the information provided by the CT image and MRI images there by providing a resultant fused image which increases the efficiency of tumor detection. We also evaluate the effectiveness of proposed algorithm on varying the wavelet fusion parameters like number of decompositions, type of wavelet used for the decomposition. The experimental results of the simulation on MRI and CT images show the performance efficiency of the proposed approach.
The theoretical tools of optical transformation and conformal mapping have enabled the transferen... more The theoretical tools of optical transformation and conformal mapping have enabled the transference of the concept of invisibility from the realms of mythology to scientific reality. A number of attempts have been made to achieve invisibility which relied on Nano or micro fabricated artificial composite material with spatially varying electro-magnetic properties. This approach limits the size of the invisibility region to a few wavelengths and is also very costly. Here, we experimentally solve this problem by designing a structure with low cost materials and simple manufacturing techniques based on the principles of refraction and lateral shift. This cloak developed is able to conceal macroscopic object of sizes of at least 3 orders of magnitude larger than the wavelength of light in all three dimensions. This clock can find huge application in defense and transformation optics.
Uploads
Papers by Vivek Angoth