Multi-scale colorectal tumour segmentation using a novel coarse to fine strategy

This paper addresses the problem of colorectal tumour segmentation in complex real world imagery. For efficient segmentation, a multi-scale strategy is developed for extracting the potentially cancerous region of interest (ROI) based on colour histograms while searching for the best texture resolution. To achieve better segmentation accuracy, we apply a novel bag-of-visual-words method based on rotation invariant raw statistical features and random projection based l2-norm sparse representation to classify tumour areas in histopathology images. Experimental results on 20 real world digital slides demonstrate that the proposed algorithm results in better recognition accuracy than several state of the art segmentation techniques.

Swift Heavy Ion Irradiation and Thermal Annealing Induced Modification of Structural, Topographical and Magnetic Properties in Monolayer and Bilayer Films Based on FeNiMoB and Zinc Ferrite

Magnetism and magnetic materials have been playing a lead role in the day to day life of human beings. The human kind owes its gratitude to the ‘lodestone’ meaning ‘leading stone’ which lead to the discovery of nations and the onset of modern civilizations. If it was William Gilbert, who first stated that ‘earth was a giant magnet’, then it was the turn of Faraday who correlated electricity and magnetism. Magnetic materials find innumerable applications in the form of inductors, read and write heads, motors, storage devices, magnetic resonance imaging and fusion reactors. Now the industry of magnetic materials has almost surpassed the semiconductor industry and this speaks volumes about its importance. Extensive research is being carried out by scientists and engineers to remove obsolescence and invent new devices. Though magnetism can be categorized based on the response of an applied magnetic field in to diamagnetic, paramagnetic, ferromagnetic, ferrimagnetic and antiferromagnetic; it is ferrimagnetic, ferromagnetic and antiferromagnetic materials which have potential applications. The present thesis focusses on these materials, their composite structures and different ways and means to modify their properties for useful applications. In the past, metals like Fe, Ni and Co were sought after for various applications though iron was in the forefront because of its cost effectiveness and abundance. Later, alloys based on Fe and Ni were increasingly employed. They were used in magnetic heads and in inductors. Ferrites entered the arena and subsequently most of the newer applications were based on ferrites, a ferrimagnetic material, whose composition can be tuned to tailor the magnetic properties. In the late 1950s a new class of magnetic material emerged on the magnetic horizon and they were fondly known as metallic glasses. They are well known for their soft magnetic properties. They were synthesized in the form of melt spun ribbons and are amorphous in nature and they are projected to replace the crystalline counterparts.

Swift Heavy Ion Irradiation and Thermal Annealing Induced Modification of Structural, Topographical and Magnetic Properties in Monolayer and Bilayer Films Based on FeNiMoB and Zinc Ferrite

Magnetism and magnetic materials have been playing a lead role in the day to day life of human beings. The human kind owes its gratitude to the ‘lodestone’ meaning ‘leading stone’ which lead to the discovery of nations and the onset of modern civilizations. If it was William Gilbert, who first stated that ‘earth was a giant magnet’, then it was the turn of Faraday who correlated electricity and magnetism. Magnetic materials find innumerable applications in the form of inductors, read and write heads, motors, storage devices, magnetic resonance imaging and fusion reactors. Now the industry of magnetic materials has almost surpassed the semiconductor industry and this speaks volumes about its importance. Extensive research is being carried out by scientists and engineers to remove obsolescence and invent new devices. Though magnetism can be categorized based on the response of an applied magnetic field in to diamagnetic, paramagnetic, ferromagnetic, ferrimagnetic and antiferromagnetic; it is ferrimagnetic, ferromagnetic and antiferromagnetic materials which have potential applications. The present thesis focusses on these materials, their composite structures and different ways and means to modify their properties for useful applications.

Interactions of Cytochrome P450 3A4 with Phospholipid Bilayer Nanodiscs

Thesis (Ph.D.)--University of Washington, 2016-08

ICTM: an interval tessellation-based model for reliable topographic segmentation

This work introduces a tessellation-based model for the declivity analysis of geographic regions. The analysis of the relief declivity, which is embedded in the rules of the model, categorizes each tessellation cell, with respect to the whole considered region, according to the (positive, negative, null) sign of the declivity of the cell. Such information is represented in the states assumed by the cells of the model. The overall configuration of such cells allows the division of the region into subregions of cells belonging to a same category, that is, presenting the same declivity sign. In order to control the errors coming from the discretization of the region into tessellation cells, or resulting from numerical computations, interval techniques are used. The implementation of the model is naturally parallel since the analysis is performed on the basis of local rules. An immediate application is in geophysics, where an adequate subdivision of geographic areas into segments presenting similar topographic characteristics is often convenient.

Typologie de la flottille chalutière du port de Sète par une méthode de segmentation

This work aims to define a typology of trawler f1eet in Sète, the main fishing harbour along the French Mediterranean coast, using several multivariate analysis methods. The fishing ships taken to account are represented by annual profiles of landing specific compositions. Five fishing strategies have been identified. A segmentation method using symbolic objects allows a formaI characterisation of the different strategies. These strategies are studied according to several general characteristics usually used for management rules elaboration (power, length, ship age). The typological analysis allows to characterise two main exploitation ways, one directed to the catch of a few species (Engraulis encrasicolus, Sardina pilchardus), the other characterised by the exploitation of a great diversity of species. By this way, it is possible to estimate how the catch of low represented species can significantly contribute to the exploitation of a resource.

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

Réseau calculant asynchrone dédié à la segmentation d'images

National audience

Deep convolutional neural networks for semantic video object segmentation

In this thesis, we propose to infer pixel-level labelling in video by utilising only object category information, exploiting the intrinsic structure of video data. Our motivation is the observation that image-level labels are much more easily to be acquired than pixel-level labels, and it is natural to find a link between the image level recognition and pixel level classification in video data, which would transfer learned recognition models from one domain to the other one. To this end, this thesis proposes two domain adaptation approaches to adapt the deep convolutional neural network (CNN) image recognition model trained from labelled image data to the target domain exploiting both semantic evidence learned from CNN, and the intrinsic structures of unlabelled video data. Our proposed approaches explicitly model and compensate for the domain adaptation from the source domain to the target domain which in turn underpins a robust semantic object segmentation method for natural videos. We demonstrate the superior performance of our methods by presenting extensive evaluations on challenging datasets comparing with the state-of-the-art methods.

Text segmentation using a cache memory

International audience

Distribution of neutral prilocaine in a phospholipid bilayer: Insights from molecular dynamics simulations

In this work, we report a 20-ns constant pressure molecular dynamics simulation of prilocaine (PLC), in amine-amide local anesthetic, in a hydrated liquid crystal bilayer of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine. The partition of PLC induces the lateral expansion of the bilayer and a concomitant contraction in its thickness. PLC molecules are preferentially found in the hydrophobic acyl chains region, with a maximum probability at similar to 12 angstrom from the center of the bilayer (between the C(4) and C(5) methylene groups). A decrease in the acyl chain segmental order parameter, vertical bar S-CD vertical bar, compared to neat bilayers, is found, in good agreement with experimental H-2-NMR studies. The decrease in vertical bar S-CD vertical bar induced by PLC is attributed to a larger accessible volume per lipid in the acyl chain region. (C) 2008 Wiley Periodicals, Inc.

High On/Off ratio memristive switching of manganite/cuprate bilayer by interfacial magnetoelectricity

Memristive switching serves as the basis for a new generation of electronic devices. Memristors are two-terminal devices in which the current is turned on and off by redistributing point defects, e.g., vacancies, which is difficult to control. Memristors based on alternative mechanisms have been explored, but achieving both the high On/Off ratio and the low switching energy desirable for use in electronics remains a challenge. Here we report memristive switching in a La_(0.7)Ca_(0.3)MnO_(3)/PrBa_(2)Cu_(3)O_(7) bilayer with an On/Off ratio greater than 103 and demonstrate that the phenomenon originates from a new type of interfacial magnetoelectricity. Using results from firstprinciples calculations, we show that an external electric-field induces subtle displacements of the interfacial Mn ions, which switches on/off an interfacial magnetic “dead” layer, resulting in memristive behavior for spin-polarized electron transport across the bilayer. The interfacial nature of the switching entails low energy cost about of a tenth of atto Joule for write/erase a “bit”. Our results indicate new opportunities for manganite/cuprate systems and other transition-metal-oxide junctions in memristive applications.

Spectral-based mesh segmentation

In design and manufacturing, mesh segmentation is required for FACE construction in boundary representation (BRep), which in turn is central for featurebased design, machining, parametric CAD and reverse engineering, among others -- Although mesh segmentation is dictated by geometry and topology, this article focuses on the topological aspect (graph spectrum), as we consider that this tool has not been fully exploited -- We preprocess the mesh to obtain a edgelength homogeneous triangle set and its Graph Laplacian is calculated -- We then produce a monotonically increasing permutation of the Fiedler vector (2nd eigenvector of Graph Laplacian) for encoding the connectivity among part feature submeshes -- Within the mutated vector, discontinuities larger than a threshold (interactively set by a human) determine the partition of the original mesh -- We present tests of our method on large complex meshes, which show results which mostly adjust to BRep FACE partition -- The achieved segmentations properly locate most manufacturing features, although it requires human interaction to avoid over segmentation -- Future work includes an iterative application of this algorithm to progressively sever features of the mesh left from previous submesh removals