Computer-based registration for digital subtraction in dental radiology.
OBJECTIVE
(1) To review computerized a posteriori techniques for geometry and contrast registration prior to digital subtraction in dental radiography; (2) to define a uniform notation for their methodological and technical classification and based on this key code; (3) to derive criteria for successful application of computer-based a posteriori registration for routine clinical subtraction.


METHODS
All techniques are classified with respect to the (1) dimension of geometry registration; (2) origin; (3) abstraction level, and (4) linkage of features used for registration of geometry; (5) elasticity; (6) domain, and (7) parameter determination of the geometrical transform used; (8) interaction of geometrical registration; as well as (9) origin of features, (10) model of transform, and (11) interaction of procedure for contrast correction.


RESULTS
With respect to clinical practicability, superior registration techniques are based on the low level abstraction of intrinsic features for both geometry and contrast registration. By approximately linking the features, a global projective transform should be generated for geometry registration by automatic methods, while automatic contrast correction should be non-parametric. This challenge is met only by one out of 36 published algorithms. Hence, although numerous computer-based techniques have been published, only a few of them are applied more than once in practice.


CONCLUSIONS
The key code proposed in this paper is useful for technical classification of a posteriori registration methods in dental radiography and allows their objective comparison. Further investigations will focus on standardization of practicable procedures to evaluate the robustness of competing methods.
Lehmann
T M
TM
Institute of Medical Informatics, Aachen University of Technology (RWTH), Aachen, Germany.
Gröndahl
H G
HG
Benn
D K
DK
D000465:Algorithms; D002965:Classification; D001330:Electronic Data Processing; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated; D011856:Radiographic Image Enhancement / Q000379:methods*; D011861:Radiography, Dental / Q000379:methods*; D012984:Software; D013382:Subtraction Technique