 |  | | | Recent advances in medical imaging now often yield multidimensional images, such as time series in functional Magnetic Resonance Imaging (fMRI), in dynamic computed tomography (CT), or in nuclear medicine (Single Photon Emission Computed Tomography - SPECT - or Positron Emission Tomography - PET). Obviously, such image series contain unique information that should help establish a diagnosis or investigate the progress of a disease. However, the images series resulting from the sophisticated new imaging devices often included tens, even hundreds of images. How can we interpret so many data in the most efficient way ? So far, the images are usually just visually interpreted, by playing a dynamic series as a movie for instance, to better grab the functional information described by the time series. Such visual analysis is obviously tedious, time-consuming, and quite challenging because of the synthesis of information that should be made by the radiologist from the whole image series. Pixies has been specifically designed to help the radiologists, the physicians and the researchers, to deal the most efficiently with large image series, by providing a tool for exploring and analysing medical image series, which features : - exploration tools for an easy analysis of 3D or 4D functional data (3D, 4D, etc), including tools that are familiar to you (like Region Of Interest drawing) as well as original tools.
- a unique methodology for synthesizing the physiological information underlying a functional image series into few images (typically from 2 to 5) representing physiological compartments and associated curves (which represent the signal change along time in each compartment). For instance, from a functional MRI including tens of images, Pixies can extract a compartment corresponding to the tissue with early vascularization, another compartment corresponding to tissues with delayed vascularization, and a third compartment corresponding to pathological tissues characterized by a specific time curve (accumulation of a tracer for instance), so summarizing tens of images by only 3 physiological images and associated curves.
- quantitative indices to characterize precisely the information underlying image series, such as time of the highest tracer concentration in a given organ for instance.
- conventional image processing operations, such as filtering, image overlay, so that you can process and visualize image series within a single software.
To better analyze, synthesize and quantify the information underlying image sequences, Pixies offers the most recent developments in image series processing using : - a software that can be run either on PC or workstations,
- a user-friendly interface that makes the software readily usable,
- a client/server mode enabling remote processing of large data sets.
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