A conceptual framework for multi-modal interactive virtual workspaces

Construction projects involve a large number of both direct stakeholders (clients, professional teams, contractors, etc.) and indirect stakeholders (local authorities, residents, workers, etc.). Current methods of communicating building design information can lead to several types of difficulties (e.g. incomplete understanding of the planned construction, functional inefficiencies, inaccurate initial work or clashes between components, etc.). Integrated software solutions based on VR technologies can bring significant value improvement and cost reduction to the Construction Industry. The aim of this paper is to present research being carried out in the frame of the DIVERCITY project (Distributed Virtual Workspace for Enhancing Communication within the Construction Industry - IST project n°13365), funded under the European IST programme (Information Society Technologies). DIVERCITY's goal is to develop a Virtual Workspace that addresses three key building construction phases: (1) Client briefing (with detailed interaction between clients and architects); (2) Design Review (which requires detailed input from multidisciplinary teams - architects, engineers, facility managers, etc.); (3) Construction (aiming to fabricate or refurbish the building).Using a distributed architecture, the DIVERCITY system aims to support and enhance concurrent engineering practices for these three phases allowing teams based in different geographic locations to collaboratively design, test and validate shared virtual projects. The global DIVERCITY project will be presented in terms of objectives and the software architecture will be detailed.149-162Pubblicat

Segmentation of brain tumors in MRI images using three-dimensional active contour without edge

Brain tumor segmentation in magnetic resonance imaging (MRI) is considered a complex procedure because of the variability of tumor shapes and the complexity of determining the tumor location, size, and texture. Manual tumor segmentation is a time-consuming task highly prone to human error. Hence, this study proposes an automated method that can identify tumor slices and segment the tumor across all image slices in volumetric MRI brain scans. First, a set of algorithms in the pre-processing stage is used to clean and standardize the collected data. A modified gray-level co-occurrence matrix and Analysis of Variance (ANOVA) are employed for feature extraction and feature selection, respectively. A multi-layer perceptron neural network is adopted as a classifier, and a bounding 3D-box-based genetic algorithm is used to identify the location of pathological tissues in the MRI slices. Finally, the 3D active contour without edge is applied to segment the brain tumors in volumetric MRI scans. The experimental dataset consists of 165 patient images collected from the MRI Unit of Al-Kadhimiya Teaching Hospital in Iraq. Results of the tumor segmentation achieved an accuracy of 89% +/- 4.7% compared with manual processes

Blurred digital mammography images : an analysis of technical recall and observer detection performance

Background: Blurred images in Full Field Digital Mammography (FFDM) are a problem in the UK Breast Screening Programme. Technical recalls may be due to blurring not being seen on lower resolution monitors used for review. Objectives: This study assesses the visual detection of blurring on a 2.3 megapixel (MP) monitor and a 5 MP report grade monitor and proposes an observer standard for the visual detection of blurring on a 5 MP reporting grade monitor. Method: Twenty-eight observers assessed 120 images for blurring; 20 had no blurring present whilst 100 had blurring imposed through mathematical simulation at 0.2, 0.4, 0.6, 0.8 and 1.0 mm levels of motion. Technical recall rate for both monitors and angular size at each level of motion were calculated. Chi-squared (X2) tests were used to test whether significant differences in blurring detection existed between 2.3 and 5 MP monitors. Results: The technical recall rate for 2.3 and 5 MP monitors are 20.3 % and 9.1% respectively. Angular size for 0.2 to 1 mm motion varied from 55 to 275 arc seconds. The minimum amount of motion for visual detection of blurring in this study is 0.4 mm. For 0.2 mm simulated motion, there was no significant difference X2 (1, N=1095) =1.61, p=0.20) in blurring detection between the 2.3 and 5 MP monitors. Conclusion: According to this study monitors equal or below 2.3 MP are not suitable for technical review of FFDM images for the detection of blur. Advances in knowledge: This research proposes the first observer standard for the visual detection of blurring. Key words: Simulated motion; technical recall; monitor resolution; observer standard; blurring detectio

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

The digital medical workflow faces many circumstances in which the images can be manipulated during viewing, extracting and exchanging. Reversible and imperceptible watermarking approaches have the potential to enhance trust within the medical imaging pipeline through ensuring the authenticity and integrity of the images to confirm that the changes can be detected and tracked. This study concentrates on the imperceptibility issue. Unlike reversibility, for which an objective assessment can be easily made, imperceptibility is a factor of human cognition that needs to be evaluated within the human context. By defining a perceptual boundary of detecting the modification, this study enables the formation of objective guidelines for the method of data encoding and level of image/pixel modification that translates to a specific watermark magnitude. This study implements a relative Visual Grading Analysis (VGA) evaluation of 117 brain MR images (8 original and 109 watermarked), modified by varying techniques and magnitude of image/pixel modification to determine where this perceptual boundary exists and relate the point at which change becomes noticeable to the objective measures of the image fidelity evaluation. The outcomes of the visual assessment were linked to the images Peak Signal to Noise Ratio (PSNR) values, thereby identifying the visual degradation threshold. The results suggest that, for watermarking applications, if a watermark is applied to the 512x512 pixel (16 bpp grayscale) images used in the study, a subsequent assessment of PSNR=82dB or greater would mean that there would be no reason to suspect that the watermark would be visually detectable. Keywords: Medical imaging; DICOM; Reversible Watermarking; Imperceptibility; Image Quality; Visual Grading Analysis

Digital watermarking : applicability for developing trust in medical imaging workflows state of the art review

Medical images can be intentionally or unintentionally manipulated both within the secure medical system environment and outside, as images are viewed, extracted and transmitted. Many organisations have invested heavily in Picture Archiving and Communication Systems (PACS), which are intended to facilitate data security. However, it is common for images, and records, to be extracted from these for a wide range of accepted practices, such as external second opinion, transmission to another care provider, patient data request, etc. Therefore, confirming trust within medical imaging workflows has become essential. Digital watermarking has been recognised as a promising approach for ensuring the authenticity and integrity of medical images. Authenticity refers to the ability to identify the information origin and prove that the data relates to the right patient. Integrity means the capacity to ensure that the information has not been altered without authorisation. This paper presents a survey of medical images watermarking and offers an evident scene for concerned researchers by analysing the robustness and limitations of various existing approaches. This includes studying the security levels of medical images within PACS system, clarifying the requirements of medical images watermarking and defining the purposes of watermarking approaches when applied to medical images