4Q 4+

View, automatically segment, analyze and label medical image tissues in 4D. Recognition training for labeling is done by the user. DICOM reader capability is built in.

The interface uses a dissection paradigm to guide placement of menu and toolbar items and the use of mouse and cursor on displayed images.Tissue objects are defined by a region of interest over image objects segmented using single touch (mouse and cursor) or a fully automatic saccadic eye movement model. Both trigger region growing to edge pixels. Object detection is automatically propagated to neighboring images for multi-image studies. The edge space I am using is defined by an article published by me in Magnetic Resonance in Medicine 37(3):418-24. 1997.

Tissue objects are labeled by creating a memory file and labeling and adding observations of object regions of interest. Object recognition discriminating power is proportional to the number of labeled observations you add. You can create as many memory files as you like.