The 3D reconstruction of medical images plays an important role in modern clinical diagnosis. Although the analytic-based, iterative-based and deep learning-based methods have been popularly used, there are still many problems to deal with. analysis-based not accurate enough, iteration-based computationally intensive, learning based heavily dependent on training data. To solve default that only...

background:   materials and methods:   results:   six cases (33.3%), followed by the mesiodens, five cases (27.8%). the canines and distomolars three cases (16.6%) each respectively, while the least were the lateral incisors and paramolars of the two cases (11.1%) each. conclusion:   population because 13 cases (72.2%) out of 18 cases had consanguineous parents, while all patients having consan...

Existing image fusion algorithms have difficulty in effectively preserving valuable target features infrared and visible images, which easily introduces blurry edges unremarkable notable targets during their process. We propose the MGFuse algorithm as a solution to this problem, is novel that utilizes multiscale decomposition optimization gradient-weighted local energy. Initially, non-subsample...

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification MRI images into normal or low grade high plays a vital role for early diagnosis. Non-Subsampled Shearlet Transform (NSST) captures more visual information than conventional wavelet transforms employed feature extraction. As space NSS...

Hyperspectral image (HSI) anomaly detection (HSI-AD) has become a hot issue in hyperspectral information processing as method for detecting undesired targets without priori against unknown background and target information, which can be better adapted to the needs of practical applications. However, demanding environment with no prior small targets, well large data high redundancy HSI itself, m...