A fuzzy logic approach to identifying brain structures in MRI using expert anatomic knowledge

Computer-assisted identification of the central sulcus in patients with brain tumors using MRI

PURPOSE

To develop computer-assisted image processing to identify the central sulcus from the MRI data sets in patients with brain tumors.

MATERIALS AND METHODS

All MR images were acquired with a 3.0 Tesla scanner by three-dimensional (3D) spoiled gradient recalled acquisition using the steady state (SPGR) gradient-echo sequence and short inversion time inversion-recovery fast spin-echo sequence. The sulci were extracted automatically from reconstructed two-dimensional images of the cortical surface of 30 patients with brain tumors, and the extracted sulci were scored according to matching of the accepted anatomical features of the central sulcus. The candidates with the three highest scores were then superimposed on the 3D images. The correct position of the central sulcus was agreed by two senior neurosurgeons and one neuroradiologist.

RESULTS

One of the three candidates corresponded to the central sulcus identified by the manual segmentation method for all 60 affected and unaffected hemispheres in the 30 patients. The candidate with the highest score coincided with the central sulcus in 26 of the 28 unaffected hemispheres and in 28 of the 32 affected hemispheres.

CONCLUSION

The proposed method of computer-assisted image processing can provide accurate guidance to identifying the central sulcus in patients with brain tumors.

Fuzzy pharmacology: theory and applications

Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

Automatic segmentation of subcortical brain structures in MR images using information fusion

This paper reports a new automated method for the segmentation of internal cerebral structures using an information fusion technique. The information is provided both by images and expert knowledge, and consists in morphological, topological, and tissue constitution data. All this ambiguous, complementary and redundant information is managed using a three-step fusion scheme based on fuzzy logic. The information is first modeled into a common theoretical frame managing its imprecision and incertitude. The models are then fused and a decision is taken in order to reduce the imprecision and to increase the certainty in the location of the structures. The whole process is illustrated on the segmentation of thalamus, putamen, and head of the caudate nucleus from expert knowledge and magnetic resonance images, in a protocol involving 14 healthy volunteers. The quantitative validation is achieved by comparing computed, manually segmented structures and published data by means of indexes assessing the accuracy of volume estimation and spatial location. Results suggest a consistent volume estimation with respect to the expert quantification and published data, and a high spatial similarity of the segmented and computed structures. This method is generic and applicable to any structure that can be defined by expert knowledge and morphological images.