SIFT is an image local feature description algorithm based on scale-space. Due to its strong
matching ability, SIFT has many applications in different fields, such as image retrieval …

Due to their robustness against large-scale geometric transformations, keypoint-based
detection methods play an important role in revealing copy–move evidence. However …

Purpose To introduce a new approach to reconstruct a 3D model of the TMJ using magnetic
resonance imaging (MRI) and cone-beam computed tomography (CBCT) registered images …

Object recognition can be done based on local feature description algorithm or through
global feature description algorithm. Both types of these descriptors have the efficiency in …

This work focuses on fully automatic detection of brain tumors. The first aim is to determine,
whether the image contains a brain with a tumor, and if it does, localize it. The goal of this …

The authors analyze the design of a method for automatized evaluation of parameters in
orthopantomographic images capturing pathological tissues developed in human jaw …

The aim of this work is to propose the fully automated pathological area extraction from multi-
parametric 2D MR images of brain. The proposed method is based on multi-resolution …

The Fuzzy C-Mean clustering (FCM) algorithm is an effective image segmentation algorithm
which combines the clustering of non-supervised and the idea of the blurry aggregate, it is …

The article reports on certain artifacts that emerge during the in vitro diffusion-weighted
imaging of physical samples. In this context, the authors analyze the influence of magnetic …

The problem most frequently encountered in the practical processing of medical images
consists in the lack of instruments enabling machine evaluation of the images. A typical …