This book explores outcome modeling in cancer from a data-centric perspective to enable a
better understanding of complex treatment response, to guide the design of advanced …

Feature extraction plays a major role in the pattern recognition process, and this paper
presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is …

Grinding and polishing are standard operations in material processing. It is important to
inspect and classify the potential defects existing on the product surfaces after grinding and …

Error Concealment (EC) techniques use either spatial, temporal or a combination of both
types of information to recover the data lost in transmitted video. In this paper, existing EC …

Convolutional Neural Networks (CNNs) have set the state-of-the-art in many computer vision
tasks in recent years. For this type of model, it is common to have millions of parameters to …

A major source of error in quantitative PET/CT scans of lung cancer tumors is respiratory
motion. Regarding the variability of PET texture features (TF), the impact of respiratory …

Scale invariant texture recognition methods are applied for the computer assisted diagnosis
of celiac disease. In particular, emphasis is given to techniques enhancing the scale …

Existing scanners produce paper images with different types of deformations such as noise,
rotation and shear. These deformations affect the accuracy of the fingerprinting the …

Unbiased internal quality classification of Chestnuts (Castanea spp.) is extremely important
to the fresh and processed industries. It can also be used as a tool for applied scientific …

This chapter describes the methods used to prepare images for further analysis, including
interest point and feature extraction. Some of these methods are also useful for global and …