Mahua Bhattacharya

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In present work we have introduced nonlinear affine registration method to incorporate the anatomic body deformation. The present technique has been developed for registration of section of human brain using CT and MR modalities. Present study related to image registration of different modality imaging is based on 2-D/2-D affine registration technique.(More)
We present a non-linear 2-D/2-D affine registration technique for MR and CT modality images of section of human brain. Automatic registration is achieved by maximization of a similarity metric, which is the correlation function of two images. The proposed method has been implemented by choosing a realistic, practical transformation and optimization(More)
The problem of feature selection consists of finding a significant feature subset of input training as well as test patterns that enable to describe all information required to classify a particular pattern. In present paper we focus in this particular problem which plays a key role in machine learning problems. In fact, before building a model for feature(More)
Medical image fusion has been used to derive the useful complimentary information from multimodal images. The prior step of fusion is registration or proper alignment of test images for accurate extraction of detail information. For this purpose, the images to be fused are geometrically aligned using mutual information (MI) as similarity measuring metric(More)
Breast cancer is one of the leading causes of death for women. Small clusters of micro calcifications appearing as collection of white spots on mammograms show an early warning of breast cancer. In present paper a novel approach of segmentation implemented on X-ray mammograms for more accurate detection of microcalcification clusters has been introduced.(More)
In present study attempt has been taken to determine the degree of malignancy of brain tumors using artificial intelligence. The suspicious regions in brain as suggested by the radiologists have been segmented using fuzzy c-means clustering technique. Fourier descriptors are utilized for precise extraction of boundary features of the tumor region. As(More)
Medical image fusion has been used to derive the useful information from multi modal medical images. The proposed methodology introduces evolutionary approaches for robust and automatic extraction of information from different modality images. This evolutionary fusion strategy implements multiresolution decomposition of the input images using wavelet(More)
Current paper presents a novel scheme for biomedical image watermarking by hiding multiple copies of the same data in the cover image using bit replacement in horizontal (HL) and vertical (LH) resolution approximation image components of wavelet domain. The proposed scheme use an approach for recovering the hidden information from the damaged copies due to(More)