Medical thermography provides an overview of the human body with two-dimensional (2D) information that assists the identification of temperature changes, based on the analysis of surface distribution. However, this approach lacks spatial depth information, which can be enhanced by adding multiple images or three-dimensional (3D) systems. Therefore, the methodology applied for this paper generates a 3D point cloud (from thermal infrared images), a 3D geometry model (from CT images), and the segmented inner anatomical structures. Thus, the following computational processing was employed: Structure from Motion (SfM), image registration, and alignment (affine transformation) between the 3D models obtained to combine and unify them. This paper presents the 3D reconstruction and visualization of the respective geometry of the neck/bust and inner anatomical structures (thyroid, trachea, veins, and arteries). Additionally, it shows the whole 3D thermal geometry in different anatomical sections (i.e., coronal, sagittal, and axial), allowing it to be further examined by a medical team, improving pathological assessments. The generation of 3D thermal anatomy models allows for a combined visualization, i.e., functional and anatomical images of the neck region, achieving encouraging results. These 3D models bring correlation of the inner and outer regions, which could improve biomedical applications and future diagnosis with such a methodology.

The study of muscle contractions generated by the muscle-tendon unit (MTU) plays a critical role in medical diagnoses, monitoring, rehabilitation, and functional assessments, including the potential for movement prediction modeling used for prosthetic control. Over the last decade, the use of combined traditional techniques to quantify information about the muscle condition that is correlated to neuromuscular electrical activation and the generation of muscle force and vibration has grown. The purpose of this review is to guide the reader to relevant works in different applications of ultrasound imaging in combination with other techniques for the characterization of biological signals. Several research groups have been using multi-sensing systems to carry out specific studies in the health area. We can divide these studies into two categories: human–machine interface (HMI), in which sensors are used to capture critical information to control computerized prostheses and/or robotic actuators, and physiological study, where sensors are used to investigate a hypothesis and/or a clinical diagnosis. In addition, the relevance, challenges, and expectations for future work are discussed.

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.