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

Full Issue: Volume 13, Issue 1 - Winter 2018

Full Issue: Volume 13, Issue 1 - Winter 201

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

Acute Stroke Multimodal Imaging: Present and Potential Applications toward Advancing Care.

In the past few decades, the field of acute ischemic stroke (AIS) has experienced significant advances in clinical practice. A core driver of this success has been the utilization of acute stroke imaging with an increasing focus on advanced methods including multimodal imaging. Such imaging techniques not only provide a richer understanding of AIS in vivo, but also, in doing so, provide better informed clinical assessments in management and treatment toward achieving best outcomes. As a result, advanced stroke imaging methods are now a mainstay of routine AIS practice that reflect best practice delivery of care. Furthermore, these imaging methods hold great potential to continue to advance the understanding of AIS and its care in the future. Copyright © 2017 by Thieme Medical Publishers, Inc

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

Numerical methods for coupled reconstruction and registration in digital breast tomosynthesis.

Digital Breast Tomosynthesis (DBT) provides an insight into the fine details of normal fibroglandular tissues and abnormal lesions by reconstructing a pseudo-3D image of the breast. In this respect, DBT overcomes a major limitation of conventional X-ray mam- mography by reducing the confounding effects caused by the superposition of breast tissue. In a breast cancer screening or diagnostic context, a radiologist is interested in detecting change, which might be indicative of malignant disease. To help automate this task image registration is required to establish spatial correspondence between time points. Typically, images, such as MRI or CT, are first reconstructed and then registered. This approach can be effective if reconstructing using a complete set of data. However, for ill-posed, limited-angle problems such as DBT, estimating the deformation is com- plicated by the significant artefacts associated with the reconstruction, leading to severe inaccuracies in the registration. This paper presents a mathematical framework, which couples the two tasks and jointly estimates both image intensities and the parameters of a transformation. Under this framework, we compare an iterative method and a simultaneous method, both of which tackle the problem of comparing DBT data by combining reconstruction of a pair of temporal volumes with their registration. We evaluate our methods using various computational digital phantoms, uncom- pressed breast MR images, and in-vivo DBT simulations. Firstly, we compare both iter- ative and simultaneous methods to the conventional, sequential method using an affine transformation model. We show that jointly estimating image intensities and parametric transformations gives superior results with respect to reconstruction fidelity and regis- tration accuracy. Also, we incorporate a non-rigid B-spline transformation model into our simultaneous method. The results demonstrate a visually plausible recovery of the deformation with preservation of the reconstruction fidelity

A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of <3 minutes per nodule. We simulated additional digital biopsies using morphological procedures. Finally, we compared the features extracted from these digital biopsies with our reference standard using intraclass correlation coefficient (ICC) to characterize robustness. Comparing the reference standard segmentations to our digital biopsies, we found that 84/94 features had an ICC >0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required