Comparative Study on Medical Image Classification Techniques

This brief study compares the proposed RGSA algorithm with other recent methods by several experiments to indicate that proposed 3DGLCM and SGLDM with SVM classifier is more efficient and accurate. The accuracy results of this study imply how well their experimental results were found to give more accurate results of classifying tumors. The center of interest for this study was made on supervised classification approaches on 2D MRI images of brain tumors. This paper gives the comparative study of various approaches that was used to identify the tumor cells with classifiers

Computed tomography image analysis for the detection of obstructive lung diseases

Damage to the small airways resulting from direct lung injury or associated with many systemic disorders is not easy to identify. Non-invasive techniques such as chest radiography or conventional tests of lung function often cannot reveal the pathology. On Computed Tomography (CT) images, the signs suggesting the presence of obstructive airways disease are subtle, and inter- and intra-observer variability can be considerable. The goal of this research was to implement a system for the automated analysis of CT data of the lungs. Its function is to help clinicians establish a confident assessment of specific obstructive airways diseases and increase the precision of investigation of structure/function relationships. To help resolve the ambiguities of the CT scans, the main objectives of our system were to provide a functional description of the raster images, extract semi-quantitative measurements of the extent of obstructive airways disease and propose a clinical diagnosis aid using a priori knowledge of CT image features of the diseased lungs. The diagnostic process presented in this thesis involves the extraction and analysis of multiple findings. Several novel low-level computer vision feature extractors and image processing algorithms were developed for extracting the extent of the hypo-attenuated areas, textural characterisation of the lung parenchyma, and morphological description of the bronchi. The fusion of the results of these extractors was achieved with a probabilistic network combining a priori knowledge of lung pathology. Creating a CT lung phantom allowed for the initial validation of the proposed methods. Performance of the techniques was then assessed with clinical trials involving other diagnostic tests and expert chest radiologists. The results of the proposed system for diagnostic decision-support demonstrated the feasibility and importance of information fusion in medical image interpretation.Open acces

Three dimensional quantitative textural analysis of nickel sulphide ore using X-ray computed tomography and grey level co-occurrence matrices on drill core

Alongside the global trend to mine and process lower grade and more mineralogically complex ores, there has been an increased awareness of the prevalence of ore heterogeneity. Ore texture - the interrelationship of minerals comprising a rock, has been identified as one of the primary geometallurgical indicators of ore variability. It is well known that a relationship exists between ore texture and the resultant metallurgical performance (ore hardness, throughput, liberation, grade, recovery). Consequently, there exists a need to rapidly, routinely, cost effectively, and reliably quantify ore texture and its variability prior to mining. This information can thereafter be incorporated into the geometallurgical block model and used for decision making informing mine planning, plant operation and optimisation, forecasting, and mine closure. The ability to rapidly, routinely, cost effectively and reliably quantify ore texture remains an ongoing challenge. In this study, the use of 3D X-ray computed tomography (XCT) is proposed as an innovative solution to non-destructively image the internal structure of drill core. Thereafter, an established, discipline independent two dimensional (2D) image analysis technique known as grey level co-occurrence matrices (GLCM) is specially adapted into three dimensions (3D) to quantify ore texture using XCT grey level volumes of drill core

Analytical electron microscopy of fine-grained phases in primitive interplanetary dust particles and carbonaceous chondrites

In order to describe the total mineralogical diversity within primitive extraterrestrial materials, individual interplanetary dust particles (IDPs) collected from the stratosphere as part of the JSC Cosmic Dust Curatorial Program were analyzed using a variety of AEM techniques. Identification of over 250 individual grains within one chondritic porous (CP) IDP shows that most phases could be formed by low temperature processes and that heating of the IDP during atmospheric entry is minimal and less than 600 C. In a review of the mineralogy of IDPs, it was suggested that the occurrence of other silicates such as enstatite whiskers is consistent with the formation in an early turbulent period of the solar nebula. Experimental confirmation of fundamental chemical and physical processes in a stellar environment, such as vapor phase condensation, nucleation, and growth by annealing, is an important aspect of astrophysical models for the evolution of the Solar System. A detailed comparison of chondritic IDP and carbonaceous chondrite mineralogies shows significant differences between the types of silicate minerals as well as the predominant oxides

Investigations of vegetation and soils information contained in LANDSAT Thematic Mapper and Multispectral Scanner data

An extension of the TM tasseled cap transformation to reflectance factor data is presented, and the basic concepts underlying the tasseled cap transformations are described. The ratio of TM bands 5 and 7, and TM tasseled cap wetness, are both shown to offer promise of direct detection of available soil moisture. Some effects of organic matter and other soil characteristics or constituents on TM tasseled cap spectral response are also considered

Workshop on Lunar Breccias and Soils and Their Meteoritic analogs

Lunar soils and breccia studies are used in studying the evolution of meteorite parent bodies. These studies are compared to lunar soils and breccias

Brain tumour grading in different MRI protocols using SVM on statistical features

In this paper a feasibility study of brain MRI dataset classification, using ROIs which have been segmented either manually or through a superpixel based method in conjunction with statistical pattern recognition methods is presented. In our study, 471 extracted ROIs from 21 Brain MRI datasets are used, in order to establish which features distinguish better between three grading classes. Thirty-eight statistical measurements were collected from the ROIs. We found by using the Leave-One-Out method that the combination of the features from the 1st and 2nd order statistics, achieved high classification accuracy in pair-wise grading comparisons