Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

INTRODUCTION In 2017, it is estimated that 26,070 patients will be diagnosed with a malignant primary brain tumor in the United States, with more than half having the diagnosis of glioblas- toma (GBM).1 Magnetic resonance imaging (MRI) is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma; standard modalities available from any clinical MRI scanner, including T1, T2, T2-FLAIR, and T1-contrast-enhanced (T1CE) sequences, provide critical clinical information. In the last decade, advanced imaging modalities are increasingly utilized to further charac- terize glioblastomas. These include multi-parametric MRI sequences, such as dynamic contrast enhancement (DCE), dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), functional imaging, and spectroscopy (MRS), to further characterize glioblastomas, and significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. A contemporary review of standard and advanced MR imaging in clinical neuro-oncologic practice is presented

Characterization and digital restauration of XIV-XV centuries written parchments by means of non-destructive techniques. Three case studies

Parchment is the primary writing medium of the majority of documents with cultural importance. Unfortunately, this material suffers of several mechanisms of degradation that affect its chemical-physical structure and the readability of text. Due to the unique and delicate character of these objects, the use of nondestructive techniques is mandatory. In this work, three partially degraded handwritten parchments dating back to the XIV-XV centuries were analyzed by means of X-ray fluorescence spectroscopy, µ-ATR Fourier transform infrared spectroscopy, and reflectance and UV-induced fluorescence spectroscopy. 'e elemental and molecular results provided the identification of the inks, pigments, and superficial treatments. In particular, all manuscripts have been written with iron gall inks, while the capital letters have been realized with cinnabar and azurite. Furthermore, multispectral UV fluorescence imaging and multispectral VIS-NIR imaging proved to be a good approach for the digital restoration of manuscripts that suffer from the loss of inked areas or from the presence of brown spotting. Indeed, using ultraviolet radiation and collecting the images at different spectral ranges is possible to enhance the readability of the text, while by illuminating with visible light and by collecting the images at longer wavelengths, the hiding effect of brown spots can be attenuated

Measuring volume of stockpile using imaging station

It is crucial to know cutting and filling volumes in many surveys, mining, quarry and engineering field of works like dredging and embankment project. Generally, volume calculation is completed using conventional surveying methods. The trapezoidal method and classical cross sectioning have been presented in the literature. In other way around, by using conventional surveying methods, the volume calculation required a lot of time, laborers and risky as the big machineries running around the work areas. Digital close range photogrammetry has been insufficient for the volume calculation of the material need to calculation of volume in risk areas or in short time. In this case, long range surveying and scanning method is an alternative method to volume calculation. By the development of scanning and imaging technologies, Topcon Imaging Station (IS) used for three dimensional modeling (3D) surveying of objects in many field such as topographic survey, mining, construction and as-built survey, etc disciplines has become a productive, faster and accurate method. This study concern is getting the stockpile volume by using Topcon IS known as advanced technology instrument which promotes both scanning and long-range surveying. The instrument, a highly-developed technology specialized with Image Master Software; distinctive software that provides capabilities to reconstructed 3D modeling after the volume data was processed. Three dimensional (3D) surfaces are created through Triangulated Irregular Network (TIN) method that supports time saving and more accurate volume calculation. The volume calculated by Image Master (IM) then compared with the volume calculated by 12D software which the data obtained by using total station and prism. The results have been analyzed with respect to different volumes, density factor, three dimensional (3D) models of stockpile and time taken for data acquisition and data processin

Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation

Copyright @ 2011 Shadi AlZubi et al. This article has been made available through the Brunel Open Access Publishing Fund.The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying region of interest (ROI) in medical images which are obtained from different medical scanners such as PET, CT, or MRI. Multiresolution analysis (MRA) using wavelet, ridgelet, and curvelet transforms has been used in the proposed segmentation system. It is particularly a challenging task to classify cancers in human organs in scanners output using shape or gray-level information; organs shape changes throw different slices in medical stack and the gray-level intensity overlap in soft tissues. Curvelet transform is a new extension of wavelet and ridgelet transforms which aims to deal with interesting phenomena occurring along curves. Curvelet transforms has been tested on medical data sets, and results are compared with those obtained from the other transforms. Tests indicate that using curvelet significantly improves the classification of abnormal tissues in the scans and reduce the surrounding noise

Lensfree computational microscopy tools for cell and tissue imaging at the point-of-care and in low-resource settings.

The recent revolution in digital technologies and information processing methods present important opportunities to transform the way optical imaging is performed, particularly toward improving the throughput of microscopes while at the same time reducing their relative cost and complexity. Lensfree computational microscopy is rapidly emerging toward this end, and by discarding lenses and other bulky optical components of conventional imaging systems, and relying on digital computation instead, it can achieve both reflection and transmission mode microscopy over a large field-of-view within compact, cost-effective and mechanically robust architectures. Such high throughput and miniaturized imaging devices can provide a complementary toolset for telemedicine applications and point-of-care diagnostics by facilitating complex and critical tasks such as cytometry and microscopic analysis of e.g., blood smears, Pap tests and tissue samples. In this article, the basics of these lensfree microscopy modalities will be reviewed, and their clinically relevant applications will be discussed

Volumetric analysis of arteriovenous malformation using computed tomographic angiography

Thesis (M.A.)--Boston UniversityAn arteriovenous malformation (AVM) is an abnormal collection of blood vessels in which arterial blood flows directly into the draining vein without the normal interposed capillaries. It is an important and growing public healthcare problem affecting millions of Americans and many more people internationally. There are several potential treatment options for the AVM, and the best treatment depends on the maximum length of nidus based on the Spetzler- Martin grading system. However, this grading system is insensitive to volume, because it was designed on the basis of two dimensional digital subtraction angiography images. Here, we report a method using computed tomographic angiography to measure the volume of AVM nidus, as a means for noninvasively assessment. The initial results show statistically significant differences between healthy and AVM subject groups in the direct comparisons of the volume (cm3) through the method we suggested (2.456 ± 1.482, 12.478 ± 5.743 and 53.963 ± 9.338 (mean ± stdev.); Normal (No AVM), Small (< 3cm), Medium (3 ~ 6 cm) respectively; P < 0.005 for all), and they also show the exponential correlation between the AVM volume and the maximum length of a nidus (trend-line: y = 4.4183e0.536x with R2 = 0.945). These results provide more accurate volumetric information. Therefore, this noninvasive imaging-based method is a promising means to measure the volume of AVM using clinically available imaging tools