The hepatocellular carcinoma (HCC) is the most frequent malignant liver tumor. Detecting the HCC evolution phases represents an important research challenge. Our aim is to discover the evolution stages of the HCC tumor, through unsupervised classification techniques, using texture-based image analysis methods. We defined the textural model of these phases, consisting of the most relevant textur...

Aging progress of a person is influenced by many factors such as genetics, health, lifestyle, and even weather conditions. Therefore human age estimation from a face image is a challenging problem. Aging causes significant variations in facial shape and texture across years. In order to construct a general age classifier, shape and texture information of human face should be used together. In t...

Image classification plays an important role in many applicable fields in our life, such as image analysis, remote sensing, and pattern recognition [9]. It can be defined as the process of sorting all the pixels in an image into a finite number of individual classes[5]. There are many types of techniques which can be used to classify and recognize different types of objects in images. For conve...

Program Authorized to Offer Degree Date In presenting this thesis in partial fulfillment of the requirements for a Master's degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this thesis is allowable only for scholarly purposes, consistent with " fair use " as prescribed in the U.S. Co...

The aim of the present study was to design, implement and evaluate a software system for discriminating between metastatic and primary brain tumors (gliomas and meningiomas) on MRI, employing textural features from routinely taken T1 post-contrast images. The proposed classifier is a modified probabilistic neural network (PNN), incorporating a non-linear least squares features transformation (L...

In this paper, we investigate a new approach to the cooccurrence matrix currently used to extract textural features: co-occurrence matrices for volumetric data. While traditional texture metrics have concentrated on 2D texture, 3D imaging modalities are becoming more and more prevalent, providing the possibility of examining texture as a volumetric phenomenon. Just as computer graphics have use...

The slopes of the Cotswolds Escarpment in the United Kingdom are mantled by extensive landslide deposits, including both relict and active features. These landslides pose a significant threat to engineering projects and have been the focus of research into the use of airborne remote sensing data sets for landslide mapping. Due to the availability of extensive ground investigation data, a test s...

Diffusion magnetic resonance imaging is presently widely used technique that allows measurement of white matter fiber orientation in the human brain. The connectivity complex of fiber tracts strongly influences the function of communicating large neuronal networks in the brain. In order to analyze the changes in white matter with respect to age, the textural features are computed from the spati...

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address th...

In this paper we present how to exploit the textural information to improve scribble-based image colorization. Although many methods have been already proposed for coloring grayscale images based on a set of color scribbles inserted by a user, very few of them take into account textural properties. We demonstrate that the textural information can be extremely helpful for this purpose and it may...