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A hybrid algorithm for medical image registration.

Sabalan Daneshvar¹, Hassan Ghassemian

¹Tarbiat Modares University of Tehran, Department of Electrical Engineering, Tehran, Iran, PO Box 14115-111. S_daneshvar@modares.ac.ir.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|February 7, 2007

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This study presents an automated method for registering computed tomography (CT) and magnetic resonance (MR) head images. The approach accurately aligns images from different systems using feature extraction and moment-based alignment.

Area of Science:

Medical Imaging
Image Processing
Computational Anatomy

Background:

Image registration aligns multiple images of the same subject.
Registering images from different modalities (e.g., CT and MR) is challenging due to varying gray values.
Simple registration methods like correlation are ineffective for cross-modality imaging.

Purpose of the Study:

To develop an automated method for registering computed tomography (CT) and magnetic resonance (MR) head images.
To address the challenge of image misalignment between different imaging systems.

Main Methods:

The proposed method involves two stages: feature extraction and feature alignment.
Features are extracted that are constant and extractable across both CT and MR imaging systems.

Related Experiment Videos

Moment-based alignment is used for feature registration, assuming only relative translation and rotation between images.

Main Results:

The automated registration method demonstrated accuracy in aligning CT and MR head images.
The technique proved robust when dealing with images from different imaging systems.

Conclusions:

The developed automated registration method is effective for CT and MR head images.
The moment-based feature alignment approach provides accurate and robust cross-modality image registration.