Multimodality Imaging Registration: A Case Study Applied to the Thyroid Graves’ Disease

Abstract

The use of different medical imaging modalities is becoming more frequently engaged in medical applications. This is mainly due to the expansion of different computational processing techniques, which facilitates not only diagnosis but also the follow-up care during medical treatments. The use of anatomical medical images, acquired by computerized tomography (CT) or magnetic resonance imaging (MRI), can be registered with the functional images of the human body, obtained by other exams, such as infrared thermography and scintigraphy. Therefore, this combination of different imaging modalities is representing an innovative perspective in medicine. The methodology presented in this paper allows the imaging fusion and achieves new 2D images, which merge different modalities altogether. The image data acquired are aligned based on the affine registration, where at least three corresponding pairs of points are selected in both images. For this purpose, it was developed a script in MATLAB®. This processing allows the combination of different pairs of images, as it also applies transparencies into them. The results obtained can grant the visualization of the thyroid and other structures of the human anatomy simultaneously into a single aligned image. In this research, the focus is to perform imaging fusion of anatomical and functional images. As example, the endocrinology case study proposed was applied for a Graves’ disease. This is a hyperthyroidism condition that causes the thyroid gland to hyper-uptakes related to the radiopharmaceuticals being used during the scintigraphy imaging. Additionally, this image was also blended with infrared thermography image, among other further combinations. Innovative results are presented based on the superposition/overlap of a pair of images, allowing physicians to evaluate both anatomical and functional images. Therefore, this paper presents the investigation of an endocrinological application improving diagnostic sensitivity.

Keywords:
Thyroid; Image Fusion; Affine Registration; Alignment; Graves’ Disease

HIGHLIGHTS

Proposed a visualization of unified images, helping the diagnosis.

Complement treatments, in a more reliable way than only single images cannot provide.

Visualization of thyroid and other structures at once in a single aligned image.

Evaluate the imaging fusion for inspection of Graves' disease.