Ontology Based Integration of Distributed and Heterogeneous Data Sources in ACGT.

In this work, we describe the set of tools comprising the Data Access Infrastructure within Advancing Clinic-genomic Trials on Cancer (ACGT), a R&D Project funded in part by the European. This infrastructure aims at improving Post-genomic clinical trials by providing seamless access to integrated clinical, genetic, and image databases. A data access layer, based on OGSA-DAI, has been developed in order to cope with syntactic heterogeneities in databases. The semantic problems present in data sources with different nature are tackled by two core tools, namely the Semantic Mediator and the Master Ontology on Cancer. The ontology is used as a common framework for semantics, modeling the domain and acting as giving support to homogenization. SPARQL has been selected as query language for the Data Access Services and the Mediator. Two experiments have been carried out in order to test the suitability of the selected approach, integrating clinical and DICOM image databases

Objective and Subjective Assessment of Digital Pathology Image Quality

The quality of an image produced by the Whole Slide Imaging (WSI) scanners is of critical importance for using the image in clinical diagnosis. Therefore, it is very important to monitor and ensure the quality of images. Since subjective image quality assessments by pathologists are very time-consuming, expensive and difficult to reproduce, we propose a method for objective assessment based on clinically relevant and perceptual image parameters: sharpness, contrast, brightness, uniform illumination and color separation; derived from a survey of pathologists. We developed techniques to quantify the parameters based on content-dependent absolute pixel performance and to manipulate the parameters in a predefined range resulting in images with content-independent relative quality measures. The method does not require a prior reference model. A subjective assessment of the image quality is performed involving 69 pathologists and 372 images (including 12 optimal quality images and their distorted versions per parameter at 6 different levels). To address the inter-reader variability, a representative rating is determined as a one-tailed 95% confidence interval of the mean rating. The results of the subjective assessment support the validity of the proposed objective image quality assessment method to model the readers’ perception of image quality. The subjective assessment also provides thresholds for determining the acceptable level of objective quality per parameter. The images for both the subjective and objective quality assessment are based on the HercepTestTM slides scanned by the Philips Ultra Fast Scanners, developed at Philips Digital Pathology Solutions. However, the method is applicable also to other types of slides and scanners