Orthorhombic distortion and orbital order in the vanadium spinel FeV2 O4

Using synchrotron and neutron diffraction measurements, we find a low-temperature orthorhombic phase in vanadium spinel FeV2O4. The orbital order of V3+ ions with tetragonal normal modes occurs at 68 K, and this leads to an appearance of the pseudotetragonal phase at a noncollinear ferrimagnetic transition temperature. Below the magnetic transition temperature, unconventional behavior of the orbital state of Fe2+ ions accompanied by the emergence of the orthorhombic phase was observed by using the normal mode analysis. We have also studied the structural properties of orbitally diluted materials. The orthorhombic phase, which is significantly affected by the other ions, is intrinsic in FeV2O4. We suggest the orthorhombic phase is strongly related with the double orbital states of Fe2+ and V3+ ions

In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection

The use of hyperspectral imaging for medical applications is becoming more common in recent years. One of the main obstacles that researchers find when developing hyperspectral algorithms for medical applications is the lack of specific, publicly available, and hyperspectral medical data. The work described in this paper was developed within the framework of the European project HELICoiD (HypErspectraL Imaging Cancer Detection), which had as a main goal the application of hyperspectral imaging to the delineation of brain tumors in real-time during neurosurgical operations. In this paper, the methodology followed to generate the first hyperspectral database of in-vivo human brain tissues is presented. Data was acquired employing a customized hyperspectral acquisition system capable of capturing information in the Visual and Near InfraRed (VNIR) range from 400 to 1000 nm. Repeatability was assessed for the cases where two images of the same scene were captured consecutively. The analysis reveals that the system works more efficiently in the spectral range between 450 and 900 nm. A total of 36 hyperspectral images from 22 different patients were obtained. From these data, more than 300 000 spectral signatures were labeled employing a semi-automatic methodology based on the spectral angle mapper algorithm. Four different classes were defined: normal tissue, tumor tissue, blood vessel, and background elements. All the hyperspectral data has been made available in a public repository

Manifold embedding and semantic segmentation for intraoperative guidance with hyperspectral brain imaging

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumour classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbour (t-SNE) approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest (STF) for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system

Use of hyperspectral/multispectral imaging in gastroenterology. Shedding some–different–light into the dark

Hyperspectral/Multispectral imaging (HSI/MSI) technologies are able to sample from tens to hundreds of spectral channels within the electromagnetic spectrum, exceeding the capabilities of human vision. These spectral techniques are based on the principle that every material has a different response (reflection and absorption) to different wavelengths. Thereby, this technology facilitates the discrimination between different materials. HSI has demonstrated good discrimination capabilities for materials in fields, for instance, remote sensing, pollution monitoring, field surveillance, food quality, agriculture, astronomy, geological mapping, and currently, also in medicine. HSI technology allows tissue observation beyond the limitations of the human eye. Moreover, many researchers are using HSI as a new diagnosis tool to analyze optical properties of tissue. Recently, HSI has shown good performance in identifying human diseases in a non-invasive manner. In this paper, we show the potential use of these technologies in the medical domain, with emphasis in the current advances in gastroenterology. The main aim of this review is to provide an overview of contemporary concepts regarding HSI technology together with state-of-art systems and applications in gastroenterology. Finally, we discuss the current limitations and upcoming trends of HSI in gastroenterology. © 2019 by the authors. Licensee MDPI, Basel, Switzerland

Acceleration of brain cancer detection algorithms during surgery procedures using GPUs

The HypErspectraL Imaging Cancer Detection (HELICoiD) European project aims at developing a methodology for tumor tissue classification through hyperspectral imaging (HSI) techniques. This paper describes the development of a parallel implementation of the Support Vector Machines (SVMs) algorithm employed for the classification of hyperspectral (HS) images of in vivo human brain tissue. SVM has demonstrated high accuracy in the supervised classification of biological tissues, and especially in the classification of human brain tumor. In this work, both the training and the classification stages of the SVMs were accelerated using Graphics Processing Units (GPUs). The acceleration of the training stage allows incorporating new samples during the surgical procedures to create new mathematical models of the classifier. Results show that the developed system is capable to perform efficient training and real-time compliant classification

Hyperspectral imaging for the detection of glioblastoma tumor cells in H&E slides using convolution neural networks

Hyperspectral imaging (HSI) technology has demonstrated potential to provide useful information about the chemical composition of tissue and its morphological features in a single image modality. Deep learning (DL) techniques have demonstrated the ability of automatic feature extraction from data for a successful classification. In this study, we exploit HSI and DL for the automatic differentiation of glioblastoma (GB) and non-tumor tissue on hematoxylin and eosin (H&E) stained histological slides of human brain tissue. GB detection is a challenging application, showing high heterogeneity in the cellular morphology across different patients. We employed an HSI microscope, with a spectral range from 400 to 1000 nm, to collect 517 HS cubes from 13 GB patients using 20× magnification. Using a convolutional neural network (CNN), we were able to automatically detect GB within the pathological slides, achieving average sensitivity and specificity values of 88% and 77%, respectively, representing an improvement of 7% and 8% respectively, as compared to the results obtained using RGB (red, green, and blue) images. This study demonstrates that the combination of hyperspectral microscopic imaging and deep learning is a promising tool for future computational pathologies

Synthesis, crystal structure, and magnetic characterization of the three-dimensional compound [Co2(cbut)(H2O) 3]n (H4cbut = 1,2,3,4- cyclobutanetetracarboxylic acid)

A novel cobalt(II) complex of formula [Co2(cbut)(H 2O)3]n (1) (H4cbut = 1,2,3,4-cyclobutanetetracarboxylic acid) has been synthesized under hydrothermal conditions and its crystal structure has been determined by means of synchrotron radiation and neutron powder diffraction. The crystal structure of 1 consists of layers of cobalt(II) ions extending in the bc-plane which are pillared along the crystallographic a-axis through the skeleton of the cbut 4- ligand. Three crystallographically independent cobalt(II) ions [Co(1), Co(2), and Co(3)] occur in 1. They are all six-coordinate with four carboxylate-oxygens [Co(1)-Co(3)] and two cis-[Co(1)] or trans-water molecules [Co(2) and Co(3)] building distorted octahedral surroundings. Regular alternating double oxo(carboxylate) [between Co(1) and Co(1a)] and oxo(carboxylate) plus one aqua and a syn-syn carboxylate bridges [between Co(1) and Co(2)] occur along the crystallographic b-axis, the values of the cobalt-cobalt separation being 3.1259(8) and 3.1555(6) Å, respectively. These chains are connected to the Co(3) atoms through the OCO carboxylate along the [01̄1] direction leading to the organic-inorganic bc-layers with Co(1)-OCO(anti-syn)-Co(3) and Co(2)-OCO(anti-anti)-Co(3) distances of 5.750(2) and 4.872(1) Å. The shortest interlayer cobalt-cobalt separation through the cbut4- skeleton along the crystallographic a-axis is 7.028(2) Å. Variable-temperature magnetic susceptibility measurements show the occurrence of antiferromagnetic ordering with a Néel temperature of 5.0 K, followed by a field-induced ferromagnetic transition under applied dc fields larger than 1500 Oe. The magnetic structure of 1 has been elucidated at low temperatures in zero field by neutron powder diffraction measurements and was found to be formed by ferromagnetic chains running along the b-axis which are antiferromagnetically coupled with the Co(3) ions through the c-axis giving rise to noncompensated magnetic moments within each bc-layer (ferrimagnetic plane). The occurrence of an antitranslation operation between these layers produces a weak interlayer antiferromagnetic coupling along the a-axis which is overcome by dc fields greater than 1500 Oe resulting in a phase transition toward a ferromagnetic state (metamagnetic behavior). © 2014 American Chemical Society.Partial funding for this work is provided by the Ministerio Español de Ciencia e Innovación through projects MAT2010-16981, CTQ2010-15364, DPI2010-21103- C04-03, MAT2011-27233-C02-02, MAT2011-25991 and “Factoría de Cristalización” (Consolider-Ingenio2010, CSD2006-00015), the Generalitat Valenciana (ISIC/2012/ 002), and the CEI Canarias: Campus Atlántico Tricontinental. P.D.-G. also thanks to Ministerio Español de Economia y Competitividad through FPI program for predoctoral contracts.Peer Reviewe