Abstract: The present invention provides a system providing a suite of functions for automatically analyzing MRI images of brains to quantitatively assess brain development in children and adolescents. The system compares MRI images of a subject's brain to a database of normal brains, identifies regions showing abnormal growth, structure, and/or morphology, and notifies the health care provider of such abnormalities. The health care provider is notified by way of a graphical image depicted on a display highlighting the abnormal area(s) of the brain.

Abstract: A method for mosaicing frames from a video sequence is disclosed. Each frame is constituted by a point cloud, and each point in the point cloud is potentially acquired at a different time. The method involves compensating for motion and motion distortion due to acquisition time differences in each frame, applying a global optimization of inter-frame registration to align consistently the frames, and applying a reconstruction algorithm on the registered frames to construct a mosaic.

Abstract: A device (D) is dedicated to the processing of data constituting initial tensor images, each tensor being a real symmetric and positive definite matrix representing an elementary part of a received tensor image. This device (D) comprises, on the one hand, a first calculating module (MC1) capable of performing a first selected, bijective and defined function of R*+ in R, and being associated with a selected metric definition, this first function allowing a second reciprocal function, and on the other, comprises a first processing module (MT1) provided for: i) constituting a first representation of a received tensor image; ii) calling the first calculating module (MC1) for applying the first function to a selected part of the first representation whereby obtaining a transformed part, and; iii) constituting, from the transformed part, a second representation of the tensor images ready to be processed.

Abstract: The present invention concerns a mosaicing method taking into account motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. The invention relates to a method for mosaicing frames from a video sequence acquired from a scanning device such as a scanning microscope, the method comprising the steps of: a) compensating for motion and motion distortion due to the scanning microscope, b) applying a global optimisation of inter-frame registration to align consistently the frames c) applying a construction algorithm on the registered frames to construct a mosaic, and d) applying a fine frame-to-mosaic non rigid registration. The method is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations.

Abstract: A mosaicing method taking into account motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. The method for mosaicing frames from a video sequence acquired from a scanning device such as a scanning microscope, includes the steps of: a) compensating for motion and motion distortion due to the scanning microscope, b) applying a global optimization of inter-frame registration to align consistently the frames c) applying a construction algorithm on the registered frames to construct a mosaic, and d) applying a fine frame-to-mosaic non rigid registration. The method is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations.

Abstract: The present invention concerns a mosaicing method taking into account motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. The invention relates to a method for mosaicing frames from a video sequence acquired from a scanning device such as a scanning microscope, the method comprising the steps of: a) compensating for motion and motion distortion due to the scanning microscope, b) applying a global optimisation of inter-frame registration to align consistently the frames c) applying a construction algorithm on the registered frames to construct a mosaic, and d) applying a fine frame-to-mosaic non rigid registration. The method is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations.

Abstract: A device (D) is dedicated to the processing of data constituting initial tensor images, each tensor being a real symmetric and positive definite matrix representing an elementary part of a received tensor image. This device (D) comprises, on the one hand, a first calculating module (MCI) capable of performing a first selected, bijective and defined function of R*+ in R, and being associated with a selected metric definition, this first function allowing a second reciprocal function, and on the other, comprises a first processing module (MT1) provided for: i) constituting a first representation of a received tensor image; ii) calling the first calculating module (MC1) for applying the first function to a selected part of the first representation whereby obtaining a transformed part, and; iii) constituting, from the transformed part, a second representation of the tensor images ready to be processed.

Abstract: A filter plate having defects that may cause image artefacts is moved during an exposure. The movement distributes the defects of the plate in the image to a point where they can no longer be seen in the image. Preferably, the shifting of the plate is done in the plane of the plate, in a direction perpendicular to the axes of the rollers used for in the manufacture of the plate.

Abstract: An electronic data processing device receives first and second data sets representing first and second comparable digital images. It comprises registration means comprising a first module which calculates a main function representative of the correlation ratios between the data of the first and second sets, and a second module which determines a registration transformation between one of the images and the other from the main function.