A proteomics-based approach for the identification of biliary markers of cholangiocarcinoma

Prognosis for patients with cholangiocarcinoma (CCA) continues to be poor as a result of the difficulty in distinguishing malignant from benign bile duct disease, late stage diagnosis and a lack of sufficiently sensitive and specific diagnostic markers. These factors underlie the pressing clinical need for novel disease biomarkers. The utility of bile as a proximal fluid for biomarker discovery (compared to serum) was investigated using two dimensional difference gel electrophoresis (2D DIGE). Significant differences between the proteomes of bile and serum were identified, supporting the hypothesis that bile offers a potentially enriched microenvironment of proteins shed/secreted by tumour. However, as with serum, a few major abundant proteins dominate the bile proteome, therefore an albumin/IgG depletion technique was optimised to improve biomarker identification. The bile proteome was initially characterised in samples from patients with hilar CCA. A protein mastermap was generated by two dimensional polyacrylamide gel electrophoresis (2D PAGE) and a catalogue of proteins by liquid chromatography – tandem mass spectrometry (LC-MS/MS), which identified 80 and 813 unique proteins respectively. This represents one of the largest compendiums to date and forms a basis for future proteomic-based biomarker studies. A comparative analysis of biliary proteins in CCA and benign biliary disease was performed using a label-free proteomic approach to identify potential diagnostic biomarker(s). Comparative analysis of bile protein profile in 5 patients with CCA versus benign biliary disease identified 13 proteins which were at higher levels in malignant disease of which metalloproteinase-9 (MMP-9), Rho GDP-dissociation inhibitor 2 (also known as Ly-GDI), Annexin A3 and pre-B-cell colony-enhancing factor (PBEF) were taken forward in immunoblotting-based validation. MMP-9 was shown to be overexpressed in bile of CCA and represents a potential diagnostic marker. In addition analysis of bile samples showed lipocalin-2 and its complex with MMP-9 were present in greater amounts in CCA compared to benign biliary disease

Objective quality metric for 3D virtual views

In free-viewpoint television (FTV) framework, due to hard-ware and bandwidth constraints, only a limited number of viewpoints are generally captured, coded and transmitted; therefore, a large number of views needs to be synthesized at the receiver to grant a really immersive 3D experience. It is thus evident that the estimation of the quality of the synthesized views is of paramount importance. Moreover, quality assessment of the synthesized view is very challeng-ing since the corresponding original views are generally not available either on the encoder (not captured) or the decoder side (not transmitted). To tackle the mentioned issues, this paper presents an algorithm to estimate the quality of the synthesized images in the absence of the corresponding ref-erence images. The algorithm is based upon the cyclopean eye theory. The statistical characteristics of an estimated cy-clopean image are compared with the synthesized image to measure its quality. The prediction accuracy and reliability of the proposed technique are tested on standard video dataset compressed with HEVC showing excellent correlation results with respect to state-of-the-art full reference image and video quality metrics. Index Terms — Quality assessment, depth image based rendering, view synthesis, FTV, HEVC 1

Image de-fencing framework with hybrid inpainting algorithm

Detection and removal of fences from digital images become essential when an important part of the scene turns to be occluded by such unwanted structures. Image de-fencing is challenging because manually marking fence boundaries is tedious and time-consuming. In this paper, a novel image de-fencing algorithm that effectively detects and removes fences with minimal user input is presented. The user is only requested to mark few fence pixels; then, color models are estimated and used to train Bayes classifier to segment the fence and the background. Finally, the fence mask is refined exploiting connected component analysis and morphological operators. To restore the occluded region, a hybrid inpainting algorithm is proposed that integrates exemplar-based technique with a pyramid-based interpolation approach. In contrast to previous solutions which work only for regular pattern fences, the proposed technique is able to remove both regular and irregular fences. A large number of experiments are carried out on a wide variety of images containing different types of fences demonstrating the effectiveness of the proposed approach. The proposed approach is also compared with state-of-the-art image de-fencing and inpainting techniques and showed convincing results. 2016, Springer-Verlag London.Scopu