Scan-Chain Intra-Cell Aware Testing

This paper first presents an evaluation of the effectiveness of different test pattern sets in terms of ability to detect possible intra-cell defects affecting the scan flip-flops. The analysis is then used to develop an effective test solution to improve the overall test quality. As a major result, the paper demonstrates that by combining test vectors generated by a commercial ATPG to detect stuck-at and delay faults, plus a fragment of extra test patterns generated to specifically target the escaped defects, we can obtain a higher intra-cell defect coverage (i.e., 6.46% on average) and a shorter test time (i.e., 42.20% on average) than by straightforwardly using an ATPG which directly targets these defects

Cone beam CT of the musculoskeletal system : clinical applications

Objectives: The aim of this pictorial review is to illustrate the use of CBCT in a broad spectrum of musculoskeletal disorders and to compare its diagnostic merit with other imaging modalities, such as conventional radiography (CR), Multidetector Computed Tomography (MDCT) and Magnetic Resonance Imaging. Background: Cone Beam Computed Tomography (CBCT) has been widely used for dental imaging for over two decades. Discussion: Current CBCT equipment allows use for imaging of various musculoskeletal applications. Because of its low cost and relatively low irradiation, CBCT may have an emergent role in making a more precise diagnosis, assessment of local extent and follow-up of fractures and dislocations of small bones and joints. Due to its exquisite high spatial resolution, CBCT in combination with arthrography may be the preferred technique for detection and local staging of cartilage lesions in small joints. Evaluation of degenerative joint disorders may be facilitated by CBCT compared to CR, particularly in those anatomical areas in which there is much superposition of adjacent bony structures. The use of CBCT in evaluation of osteomyelitis is restricted to detection of sequestrum formation in chronic osteomyelitis. Miscellaneous applications include assessment of (symptomatic) variants, detection and characterization of tumour and tumour-like conditions of bone. Teaching Points: Review the spectrum of MSK disorders in which CBCT may be complementary to other imaging techniques. Compare the advantages and drawbacks of CBCT compared to other imaging techniques. Define the present and future role of CBCT in musculoskeletal imaging

Patch-based Convolutional Neural Network for Whole Slide Tissue Image Classification

Convolutional Neural Networks (CNN) are state-of-the-art models for many image classification tasks. However, to recognize cancer subtypes automatically, training a CNN on gigapixel resolution Whole Slide Tissue Images (WSI) is currently computationally impossible. The differentiation of cancer subtypes is based on cellular-level visual features observed on image patch scale. Therefore, we argue that in this situation, training a patch-level classifier on image patches will perform better than or similar to an image-level classifier. The challenge becomes how to intelligently combine patch-level classification results and model the fact that not all patches will be discriminative. We propose to train a decision fusion model to aggregate patch-level predictions given by patch-level CNNs, which to the best of our knowledge has not been shown before. Furthermore, we formulate a novel Expectation-Maximization (EM) based method that automatically locates discriminative patches robustly by utilizing the spatial relationships of patches. We apply our method to the classification of glioma and non-small-cell lung carcinoma cases into subtypes. The classification accuracy of our method is similar to the inter-observer agreement between pathologists. Although it is impossible to train CNNs on WSIs, we experimentally demonstrate using a comparable non-cancer dataset of smaller images that a patch-based CNN can outperform an image-based CNN

The molecular landscape of colitis-associated carcinogenesis

In spite of the well-established histopathological phenotyping of IBD-associated preneoplastic and neoplastic lesions, their molecular landscape remains to be fully elucidated. Several studies have pinpointed the initiating role of longstanding/relapsing inflammatory insult on the intestinal mucosa, with the activation of different pro-inflammatory cytokines (TNF-\u3b1, IL-6, IL-10, IFN-\u3b3), chemokines and metabolites of arachidonic acid resulting in the activation of key transcription factors such as NF-\u3baB. Longstanding inflammation may also modify the intestinal microbiota, prompting the overgrowth of genotoxic microorganisms, which may act as further cancer promoters. Most of the molecular dysregulation occurring in sporadic colorectal carcinogenesis is documented in colitis-associated adenocarcinoma too, but marked differences have been established in both their timing and prevalence. Unlike sporadic cancers, TP53 alterations occur early in IBD-related carcinogenesis, while APC dysregulation emerges mainly in the most advanced stages of the oncogenic cascade. From the therapeutic standpoint, colitis-associated cancers are associated with a lower prevalence of KRAS mutations than the sporadic variant. Epigenetic changes, including DNA methylation, histone modifications, chromatin remodeling, and non-coding RNAs, are significantly involved in colitis-associated cancer development and progression. The focus now is on identifying diagnostic and prognostic biomarkers, with a view to ultimately designing patient-tailored therapie

volumetric characterisation and correlation to established classification systems

Objective and sensitive assessment of cartilage repair outcomes lacks suitable methods. This study investigated the feasibility of 3D ultrasound biomicroscopy (UBM) to quantify cartilage repair outcomes volumetrically and their correlation with established classification systems. 32 sheep underwent bilateral treatment of a focal cartilage defect. One or two years post- operatively the repair outcomes were assessed and scored macroscopically (Outerbridge, ICRS-CRA), by magnetic resonance imaging (MRI, MOCART), and histopathology (O'Driscoll, ICRS-I and ICRS-II). The UBM data were acquired after MRI and used to reconstruct the shape of the initial cartilage layer, enabling the estimation of the initial cartilage thickness and defect volume as well as volumetric parameters for defect filling, repair tissue, bone loss and bone overgrowth. The quantification of the repair outcomes revealed high variations in the initial thickness of the cartilage layer, indicating the need for cartilage thickness estimation before creating a defect. Furthermore, highly significant correlations were found for the defect filling estimated from UBM to the established classification systems. 3D visualisation of the repair regions showed highly variable morphology within single samples. This raises the question as to whether macroscopic, MRI and histopathological scoring provide sufficient reliability. The biases of the individual methods will be discussed within this context. UBM was shown to be a feasible tool to evaluate cartilage repair outcomes, whereby the most important objective parameter is the defect filling. Translation of UBM into arthroscopic or transcutaneous ultrasound examinations would allow non-destructive and objective follow-up of individual patients and better comparison between the results of clinical trials