Role of correlated noise in textural features extraction

Abstract Gadolinite [REE2Fe2+Be2Si2O10] is a common mineral in certain types of rare element and rare earth element (REL-REE) pegmatites. Changes in pegmatite environment during and after gadolinite formation may be devised by studying its crystal-chemical properties and a thorough observation of microfeatures in the mineral matrix. Post-crystallization processes in pegmatite might trigger alteration mechanisms in gadolinite like in other REE-rich pegmatite minerals, whereby various late-magmatic or metasomatic events may aﬀect mineral chemistry. Three gadolinite samples originating from various pegmatite occurrences in southern Norway oﬀer an excellent opportunity in studying post-crystallization evolution of the pegmatites; by determining their crystallographic, chemical, and micro-textural features, imprints of the related processes in the pegmatites have been characterized in this study. Relevant mineral information was collected in recrystallization experiments of fully or slightly metamictized gadolinite samples and subsequent XRD analyses. Micro-Raman spectroscopy, electron microprobe analysis (EMPA), and scanning electron microscope–backscattered electron–energy-dispersive X-ray spectroscopy (SEM-BSE-EDS) analyses were employed to retrieve micro-chemical properties and related micro-textural features of the mineral matrix. With a reference to the gadolinite supergroup, a general alteration path can be envisaged outlining the pegmatite evolution and suggesting the occurrence of the secondary REE mineral phases: altered gadolinite domains prove Ca enrichment with a tendency toward the hingganite composition, while a slight fluorine increase and sporadic secondary fluorite occurrence imply a significant role of fluorine as a complexing agent in the dissolution-reprecipitation mechanism of metasomatic alteration in the mineral. Micro-Raman spectra show improved vibration statistics for the altered gadolinite domains, which could be linked to the substitution of rare earth elements (REE) by Ca and a possible increase of structural ordering within the gadolinite structure, being at the same time an indication of structural healing of metamictized domains by metasomatic processes. A study of microfeatures in the complex silicates like gadolinite proves to be an excellent tool to trace post-crystallization processes in a pegmatitic environment. With a slight redistribution of radionuclides during an alteration in gadolinite, a moderate precaution has to be taken when selecting gadolinite for U-Th-Pb dating.

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Mineral replacement reactions: from macroscopic observations to microscopic mechanisms

Mineralogical Magazine ◽

10.1180/0026461026650056 ◽

2002 ◽

Vol 66 (5) ◽

pp. 689-708 ◽

Cited By ~ 616

Author(s):

A. Putnis

Keyword(s):

Mineral Assemblage ◽

Chemical Weathering ◽

Fluid Phase ◽

Textural Features ◽

Metamorphic Fluid ◽

Common Features ◽

Solid Phases ◽

Mineral Replacement ◽

Relative Solubility

AbstractMineral replacement reactions take place primarily by dissolution-reprecipitation processes. Processes such as cation exchange, chemical weathering, deuteric alteration, leaching, pseudomorphism, metasomatism, diagenesis and metamorphism are all linked by common features in which one mineral or mineral assemblage is replaced by a more stable assemblage. The aim of this paper is to review some of these aspects of mineral replacement and to demonstrate the textural features they have in common, in order to emphasize the similarities in the underlying microscopic mechanisms. The role of volume change and evolution of porosity is explored both from natural microtextures and new experiments on model replacement reactions in simple salts. It is shown that the development of porosity is often a consequence of mineral replacement processes, irrespective of the relative molar volumes of parent and product solid phases. The key issue is the relative solubility of the phases in the fluid phase. Concepts such as coupled dissolution-precipitation, and autocatalysis are important in understanding these processes. Some consequences of porosity generation for metamorphic fluid flow as well as subsequent crystal growth are also discussed.

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Prognostic Role Of Computed Tomography Textural Features In Early-Stage Non-Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy

Cancer Management and Research ◽

10.2147/cmar.s220587 ◽

2019 ◽

Vol Volume 11 ◽

pp. 9921-9930 ◽

Cited By ~ 1

Author(s):

Ran Zhang ◽

Changbin Wang ◽

Kai Cui ◽

Yicong Chen ◽

Fenghao Sun ◽

...

Keyword(s):

Computed Tomography ◽

Lung Cancer ◽

Cancer Patients ◽

Early Stage ◽

Small Cell ◽

Textural Features ◽

Small Cell Lung ◽

Prognostic Role ◽

Lung Cancer Patients

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Glioma Segmentation and Classification System Based on Proposed Texture Features Extraction Method and Hybrid Ensemble Learning

Traitement du signal ◽

10.18280/ts.370611 ◽

2020 ◽

Vol 37 (6) ◽

pp. 989-1001

Author(s):

Kirti Raj Bhatele ◽

Sarita Singh Bhadauria

Keyword(s):

Random Forest ◽

Extraction Method ◽

Texture Features ◽

Features Extraction ◽

Automated System ◽

Discrete Wavelet ◽

Low Grade ◽

Textural Features ◽

Ensemble Model ◽

Run Length

This paper presents an efficient and accurate automated system based on the hybrid XGBoost with Random forest (XGBRF) ensemble model in order to classify the Glioma (type of mostly diagnosed brain tumor) into low grade and high grade Glioma. In this approach initially global thresholding is employed on various MRI sequence and their fusion combinations in order to perform the accurate segmentation. Then uses a proposed Enhanced wavelet binary pattern run length matrix method (EWBPRL) for textural features extraction from the region of interest or segmented Glioma tumor region. This proposed feature extraction method is based on the Discrete wavelet transform (DWT), Local Binary pattern (LBP) and Gray level run length Matrix (GLRLM) methods to extract texture features from the segmented region. Some morphological features are also computed from the segmented region along the textural features. Finally both these extracted features are employed in order to train a hybrid XGBoost with Random forest ensemble model for the first time. The proposed automated system apart from accurately detecting and segmenting the tumors region from the fused MRI sequences, also tends to determine the grading of Glioma in terms of severity. The proposed system is evaluated on the large size balance local dataset and as well as on the popular global datasets like BRATS 2013 and BRATS 2015. This approach offers an encouraging accuracy of 99.25% on the local dataset with the fusion of T1C+T2+Flair MRI sequence as compare to 96.75% accuracy, which is achieved utilizing the fusion of T1+T1C+T2+Flair MRI sequence.

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Inferring decoding strategies for multiple correlated neural populations

10.1101/108019 ◽

2017 ◽

Cited By ~ 1

Author(s):

Kaushik J Lakshminarasimhan ◽

Alexandre Pouget ◽

Gregory C DeAngelis ◽

Dora E Angelaki ◽

Xaq Pitkow

Keyword(s):

Neural Coding ◽

Large Scale ◽

Brain Area ◽

Mathematical Framework ◽

Correlated Noise ◽

Neural Basis ◽

Brain Areas ◽

Precise Knowledge ◽

Behaving Monkeys

AbstractStudies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional role of brain areas. Theories that focus only on choice-related neuronal activity cannot reconcile those findings without additional experiments involving large-scale recordings to measure interneuronal correlations. By expanding current theories of neural coding and incorporating results from inactivation experiments, we demonstrate here that it is possible to infer decoding weights of different brain areas without precise knowledge of the correlation structure. We apply this technique to neural data collected from two different cortical areas in macaque monkeys trained to perform a heading discrimination task. We identify two opposing decoding schemes, each consistent with data depending on the nature of correlated noise. Our theory makes specific testable predictions to distinguish these scenarios experimentally without requiring measurement of the underlying noise correlations.Author SummaryThe neocortex is structurally organized into distinct brain areas. The role of specific brain areas in sensory perception is typically studied using two kinds of laboratory experiments: those that measure correlations between neural activity and reported percepts, and those that inactivate a brain region and measure the resulting changes in percepts. The two types of experiments have generally been interpreted in isolation, in part because no theory has been able combine their outcomes. Here, we describe a mathematical framework that synthesizes both kinds of results, giving us a new way to assess how different brain areas contribute to perception. When we apply our framework to experiments on behaving monkeys, we discover two models that can explain the perplexing finding that one brain area can predict an animal’s percepts, even though the percepts are not affected when that brain area is inactivated. The two models ascribe dramatically different efficiencies to brain computation. We show that these two models can be distinguished by an experiment that measures correlations while inactivating different brain areas.

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Synneusis: does its preservation imply magma mixing?

Mineralogia ◽

10.2478/mipo-2018-0009 ◽

2018 ◽

Vol 49 (1-4) ◽

pp. 99-117 ◽

Cited By ~ 2

Author(s):

Bibhuti Gogoi ◽

Ashima Saikia

Keyword(s):

Magma Mixing ◽

Mafic Magma ◽

Textural Features ◽

Magmatic Evolution ◽

Mafic Rocks ◽

Intermediate Rock ◽

Euhedral Crystal ◽

Mineral Compositions ◽

Felsic Rocks

Abstract The Ghansura Felsic Dome (GFD) occurring in the Bathani volcano-sedimentary sequence was intruded by mafic magma during its evolution leading to magma mixing. In addition to the mafic and felsic rocks, a porphyritic intermediate rock occurs in the GFD. The study of this rock may significantly contribute toward understanding the magmatic evolution of the Ghansura dome. The porphyritic rock preserves several textures indicating its hybrid nature, i.e. that it is a product of mafic-felsic magma mixing. Here, we aim to explain the origin of the intermediate rock with the help of textural features and mineral compositions. Monomineralic aggregates or glomerocrysts of plagioclase give the rock its characteristic porphyritic appearance. The fact that the plagioclase crystals constituting the glomerocrysts are joined along prominent euhedral crystal faces suggests the role of synneusis in the formation of the glomerocrysts. The compositions of the glomerocryst plagioclases are similar to those of plagioclases in the mafic rocks. The results from this study indicate that the porphyritic intermediate rock formed by the mixing of a crystal-rich mafic magma and a crystal-poor felsic melt.

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