Limb volume measurements are used for evaluating growth of muscle mass and effectivity of strength training. Beside sport sciences, it is used e.g. for detection of oedemas, lymphedemas or carcinomas or for examinations of muscle atrophy. There are several commonly used methods, but there is a lack of clear comparison, which shows their advantages and limits. The accuracy of each method is uncertainly estimated only. The aim of this paper is to determine and experimentally verify their accuracy and compare them among each other. Water Displacement Method (WD), three methods based on circumferential measures—Frustum Sign Model (FSM), Disc Model (DM), Partial Frustum Model (PFM) and two 3D scan based methods Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) were compared. Precise reference cylinders and limbs of two human subjects were measured 10 times by each method. Personal dependency of methods was also tested by measuring 10 times the same object by 3 different people. Accuracies: WD 0.3 %, FSM 2–8 % according person, DM, PFM 1–8 %, MRI 2 % (hand) or 8 % (finger), CT 0.5 % (hand) or 2 % (finger);times: FSM 1 min, CT 7 min, WD, DM, PFM 15 min, MRI 19 min; and more. WD was found as the best method for most of uses with best accuracy. The CT disposes with almost the same accuracy and allows measurements of specific regions (e.g. particular muscles), as same as MRI, which accuracy is worse though, but it is not harmful. Frustum Sign Model is usable for very fast estimation of limb volume, but with lower accuracy, Disc Model and Partial Frustum Model is useful in cases when Water Displacement cannot be used.

There are special medical cases, where standard medical imaging modalities are able to offer sufficient results, but not in the optimal way. It means, that desired results are produced with unnecessarily high expenses, with redundant informations or with needless demands on patient. This paper deals with one special case, where information useful for examination is the body surface only, inner sight into the body is needless. New specialized medical imaging device is developed for this situation. In the Introduction section, analysis of presently used medical imaging modalities is presented, which declares, that no available imaging device is best fitting for mentioned purposes. In the next section, development of the new specialized medical imaging device is presented, and its principles and functions are described. Then, the parameters of new device are compared with present ones. It brings significant advantages comparing to present imaging systems.

This paper deals with application of 3D scanning technology in medicine. Important properties of 3D scanners are discussed with emphasize on medical applications. Construction of medical 3D scanner according to these specifications is described and practical application of its use in medical volumetry is presented. Besides volumetry, such 3D scanner is usable for many other purposes, like monitoring of recovery process, ergonomic splint manufacturing or inflammation detection. 3D scanning introduces novel volumetric method, which is compared with standard methods. The new method is more accurate compared to present ones. Principles of this method are discussed in paper and its accuracy is evaluated and experimentally verified.

Objectives. At present, medical thermal imaging is still considered a mere qualitative tool enabling us to distinguish between but lacking the ability to quantify the physiological and nonphysiological states of the body. Such a capability would, however, facilitate solving the problem of medical quantification, whose presence currently manifests itself within the entire healthcare system. Methods. A generally applicable method to enhance captured 3D spatial data carrying temperature-related information is presented; in this context, all equations required for other data fusions are derived. The method can be utilized for high-density point clouds or detailed meshes at a high resolution but is conveniently usable in large objects with sparse points. Results. The benefits of the approach are experimentally demonstrated on 3D thermal scans of injured subjects. We obtained diagnostic information inaccessible via traditional methods. Conclusion. Using a 3D model and thermal image data fusion allows the quantification of inflammation, facilitating more precise injury and illness diagnostics or monitoring. The technique offers a wide application potential in medicine and multiple technological domains, including electrical and mechanical engineering.

Motion Capture (MoCap) is rapidly growing in the sports, biomechanics, healthcare, and medicine segments, where accuracy is crucial. Current research studies are concurrently confirming that the accuracy can be determined only for the specific analyzed configuration and thus recommending performing your own accuracy verification on your specific setup. However, it is often hard to perform since it requires significant effort, time, knowledge of statistical data analysis and often equipment and tools that are not commonly available. This paper deals with this by creating a standardized setup with carefully evaluated accuracy, substituting the on-site validation process (in case of using such a setup) or providing the worst-case accuracy (when a more advanced setup is used). The setup is designed to be low-cost, easily reproducible and cover a wide range of applications – thus VICON setup with five VERO v1.3 cameras is used. The accuracy was evaluated using the robotic manipulator EPSON C3, determining that the absolute positioning accuracy of such a standardized setup is 0.65 mm on average (SD = 0.48, with maximal error of 2.47 mm) and rotation accuracy 0.40° (SD = 0.35, with maximal error of 2.0°), which is negligible considering the experimental diameter of 1.4 m and full angular span. The major source of error was specific to particular spatial and rotational positions; other systematic and other random errors were noticeably smaller. If the standardized setup is used and all its requirements are met, a similar accuracy as validated above can be expected without the need to explicitly validate the specific configuration, which is time-consuming and resource-intensive.