Gallery
Properly transformed, insight and value can be liberated from data that is bound up in tables. These images are taken from the case examples described throughout this website.
 | Magnetic field readings from a non-contact sensor system. This system works by fusing
data from three sensors with overlapping coverage areas. The fused data is then transformed
into a precise reading of position in three dimensional space. The animation is produced by the varying the distance between the sensor and target. |
 | Left: MRI image of cartoid artery with plaque thickening. Right a transformation of the same image into 'lesion space' |
 | 3 D rendering of pattern recognition algorithms to detect plaque. |
 | Slice and axial view of carotid artery MRI. Red outline indicates same location in two different views. |
 | Non-contact magnetic sensor detects periodic motion that accompanies vibratory movement. 80 milliseconds of motion is captured in this sequence that covers several cycles of motion. Diagnostic algorithms can be applied to identify failure modes that may be associated with vibratory pattern. |
 | Company logo. Black and white image taken from MRI scan. Image manipulated to illustrate how medical image registration works. |
 | Surface rendering of carotid artery following transformation into 'lesion space'. The black points indicate tissue border as determined by an automated tracing algorithm. The spatial transformation allows a simplified and more robust expression of the tracing algorithm. |
 | Layout pattern and coverage areas for magnetic non-contact sensor system. |
 | 3D scatter plot of tissue features following PCA transformation. Tissue clusters fall into distinct color coded clusters. |
 | Animation of non-contact sensor movement as detected during 80 milliseconds of vibration. |
 | EPI MRI scan of human brain during test for deception. |
 | Sensor in magnetic field |
 | Morphological transform (link) |