Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

Resolution of isomeric multi-ruthenated porphyrins by travelling wave ion mobility mass spectrometry

The ability of travelling wave ion mobility mass spectrometry (TWIM-MS) to resolve cationic meta/para and cis/trans isomers of mono-, di-, tri- and tetra-ruthenated supramolecular porphyrins was investigated. All meta isomers were found to be more compact than the para isomers and therefore mixtures of all isomeric pairs could be properly resolved with baseline or close to baseline peak-to-peak resolution (Rp-p). Di-substituted cis/trans isomers were found, however, to present very similar drift times and could not be resolved. N-2 and CO2 were tested as the drift gas, and similar a but considerably better values of R-p and Rp-p were always observed for CO2. Copyright (C) 2012 John Wiley & Sons, Ltd.

A high-resolution Holocene record on the Southern Brazilian shelf: Paleoenvironmental implications

A high-resolution, multi-proxy record has been used to determine the environmental changes during the Holocene on the southern Brazilian shelf Present oceanographic conditions reveal wind and freshwater input as the determinants of short-term productivity changes in the study area. Magnetic susceptibility and grain-size variations, together with proxies of productivity (organic carbon, carbon accumulation rate, Ba, Sr, and Ca content, Ba/Al, Ba/Ti, and Al/Ti ratios) were analyzed and compared with proxies of redox condition (V/Ti ratio), terrigenous input (Fe/Ca and Ti/Ca ratios), as well as other Element/Ti ratios, to evaluate the paleoceanographic and paleoclimatic changes over the period. The core covers a time interval of about 7650 years, with sedimentation rates varying from 0.025 to 0.250 cm a(-1), which represent time intervals of between 8 and 80 a per sample. There is a clear change in the sedimentation rate at about 2800 B.P. All grain-size and elemental results indicate the occurrence of conspicuous changes between 5200 and 5000 cal. B.P., as well as between 3000 and 2800 cal. B.P. A comparison of the results with the palynological information available from the adjacent continental areas suggests that the sedimentary changes in this last interval may be correlated with the onset of modern climatic conditions in South America, and especially, with the onset of the Plata Plume Water, a water mass that carries cold, less saline waters towards the north. However, minor changes are observed at ca. 1500 B.P. and are correlated with an increase in the atmospheric humidity. Furthermore, a time-series analysis undertaken using several proxies indicated the occurrence of Sub-Milankovitch cycles, which may be compared with those reported worldwide. (C) 2008 Elsevier Ltd and INQUA. All rights reserved.

Multi-q pattern analysis: A case study in image classification

This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shannon entropy for general pattern recognition, and proposes a multi-q approach to improve pattern analysis using entropy. A series of experiments were carried out for the problem of classifying image patterns. Given a dataset of 40 pattern classes, the goal of our image case study is to assess how well the different entropies can be used to determine the class of a newly given image sample. Our experiments show that the Tsallis entropy using the proposed multi-q approach has great advantages over the Boltzmann-Gibbs-Shannon entropy for pattern classification, boosting image recognition rates by a factor of 3. We discuss the reasons behind this success, shedding light on the usefulness of the Tsallis entropy and the multi-q approach. (C) 2012 Elsevier B.V. All rights reserved.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.