3D imaging approaches based on X-ray microcomputed tomography (microCT) have become increasingly accessible with advancements in methods, instruments and expertise. The synergy of material and life sciences has impacted biomedical research by proposing new tools for investigation. However, data sharing remains challenging as microCT files are usually in the range of gigabytes and require specific and expensive software for rendering and interpretation. Here, we provide an advanced method for visualisation and interpretation of microCT data with small file formats, readable on all operating systems, using freely available Portable Document Format (PDF) software. Our method is based on the conversion of volumetric data into interactive 3D PDF, allowing rotation, movement, magnification and setting modifications of objects, thus providing an intuitive approach to analyse structures in a 3D context. We describe the complete pipeline from data acquisition, data processing and compression, to 3D PDF formatting on an example of craniofacial anatomical morphology in the mouse embryo. Our procedure is widely applicable in biological research and can be used as a framework to analyse volumetric data from any research field relying on 3D rendering and CT-biomedical imaging.

• MeSH
• anatomické modely MeSH
• automatizované zpracování dat MeSH
• komprese dat statistika a číselné údaje   MeSH
• lebka anatomie a histologie   embryologie   MeSH
• myši MeSH
• obličejové kosti anatomie a histologie   embryologie   MeSH
• rentgenová mikrotomografie statistika a číselné údaje   MeSH
• rentgenový obraz - interpretace počítačová MeSH
• šíření informací metody   MeSH
• software * MeSH
• zobrazování trojrozměrné statistika a číselné údaje   MeSH
• zvířata MeSH
• Check Tag
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Three-dimensional (3D) sonography is the next logical step in diagnostic ultrasound examination. The true value of 3D ultrasonography, however, becomes evident only if 3D structures can be assessed without preconceptions ensuing from 2D interpretations. 3D ultrasonography can greatly improve our understanding of locomotor apparatus anatomy and pathology. The authors used spatial analysis to evaluate the data obtained by examination of patients with orthopedic diagnoses. The Voluson 530 MT and SONOReal system were used for examination. The Voluson permits a choice of either a 2D or a 3D imaging program for musculoskeletal system examination. The SONOReal, owing to a positional sensor of the probe, can be attached to any ultrasound transducer. In the period from 1990 to 2004, a total of 19 000 patients were examined by ultrasonography and, in 6 500 of them, the diagnosis was verified by another method, which showed a 99 % reliability of ultrasound examination. In 350 patients 2D imaging was followed by 3D examination; in 53 of them, 3D coronal and multiplanar imaging made the diagnosis based on 2D imaging more accurate and, in 12 patients, it provided new information on the patient's diagnosis. 3D reconstructions were made in 101 patients, of these 40 had been examined by other imaging methods (magnetic resonance, computer-assisted tomography) or arthroscopy. The results of examination showed a 100% correlation. Spatial reconstruction is based on the volume rendering method. This is an extension of the planar reconstruction method. Additional image processing techniques are used for a region of interest within a 3D volume data set. 3D ultrasound revealed a spatial relationship between lesions and their surfaces. The surface mode requires that the interface between tissues with different acoustic impedances should be a start line of 3D rendering. The acoustic threshold is a condition that restricts imaging circumstances in which surface rendering will be successful. Exploring 3D reconstructions with power Doppler scanning, which is more sensitive for tracking vessels, is a unique technique that can hardly be compared with any other imaging modality. 3D-volume imaging gives the examiner freedom to generate anatomical views from an infinite number of perspectives and allows us to explore anatomic relationships in the ways not available in any conventional 2D imaging. A spatial reconstruction presents a nearly perfect anatomical model. The possibility of storing volume data is considered a further progressive trend. It greatly contributes to enhancement of the scope of follow-up examinations, permits comparisons of expert conclusions and can serve educational purposes. The digital technology offers various networking solutions and plays a role in the development of 3D telemedicine. Although the diagnostic efficacy of 3D imaging is not greatly enhanced when compared with a 2D examination done by a well-trained specialist, the features of coronary sections and spatial reconstructions represent great progress of this imaging technology.

• MeSH
• lidé MeSH
• muskuloskeletální systém diagnostické zobrazování   MeSH
• počítačové zpracování obrazu MeSH
• ultrasonografie MeSH
• zobrazování trojrozměrné * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

This paper focuses on the method for creating 3-dimensional (3D) digital models extracted from patient- specific scans of the brain. The described approach consists of several cross-platform stages: raw data segmentation, data correction in 3D-modelling software, post-processing of the 3D digital models and their presentation on an interactive web-based platform. This method of data presentation offers a cost and time effective option to present medical data accurately. An important aspect of the process is using real patient data and enriching the traditional slice-based representation of the scans with 3D models that can provide better understanding of the organs' structures. The resulting 3D digital models also form the basis for further processing into different modalities, for example models in Virtual Reality or 3D physical model printouts. The option to make medical data less abstract and more understandable can extend their use beyond diagnosis and into a potential aid in anatomy and patient education. The methods presented in this paper were originally based on the master thesis 'Transparent Minds: Testing for Efficiency of Transparency in 3D Physical and 3D Digital Models', which focussed on creating and comparing the efficiency of transparent 3D physical and 3D digital models from real-patient data.

• Klíčová slova
• 3D models, Alzheimer’s disease, data segmentation, medical art, medical visualization, patient data,
• MeSH
• anatomické modely * MeSH
• lidé MeSH
• mozek MeSH
• software MeSH
• virtuální realita * MeSH
• zobrazování trojrozměrné metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Although the field of sleep study has greatly developed over recent years, the most common and efficient way to detect sleep issues remains a sleep examination performed in a sleep laboratory. This examination measures several vital signals by polysomnograph during a full night's sleep using multiple sensors connected to the patient's body. Nevertheless, despite being the gold standard, the sensors and the unfamiliar environment's connection inevitably impact the quality of the patient's sleep and the examination itself. Therefore, with the novel development of accurate and affordable 3D sensing devices, new approaches for non-contact sleep study have emerged. These methods utilize different techniques to extract the same breathing parameters but with contactless methods. However, to enable reliable remote extraction, these methods require accurate identification of the basic region of interest (ROI), i.e., the patient's chest area. The lack of automated ROI segmenting of 3D time series is currently holding back the development process. We propose an automatic chest area segmentation algorithm that given a time series of 3D frames containing a sleeping patient as input outputs a segmentation image with the pixels that correspond to the chest area. Beyond significantly speeding up the development process of the non-contact methods, accurate automatic segmentation can enable a more precise feature extraction. In addition, further tests of the algorithm on existing data demonstrate its ability to improve the sensitivity of a prior solution that uses manual ROI selection. The approach is on average 46.9% more sensitive with a maximal improvement of 220% when compared to manual ROI. All mentioned can pave the way for placing non-contact algorithms as leading candidates to replace existing traditional methods used today.

• Klíčová slova
• 3D data processing, Breathing analysis, Depth sensors, Human-machine interaction, MS Kinect data acquisition, Segmentation,
• MeSH
• algoritmy * MeSH
• dýchání MeSH
• lidé MeSH
• počítačové zpracování obrazu metody   MeSH
• polysomnografie MeSH
• spánek MeSH
• zobrazování trojrozměrné * metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND AND OBJECTIVE: We present a fully automatic system based on learning approaches, which aims to localization and identification (labeling) of vertebrae in 3D computed tomography (CT) scans of possibly incomplete spines in patients with bone metastases and vertebral compressions. METHODS: The framework combines a set of 3D algorithms for i) spine detection using a convolution neural network (CNN) ii) spinal cord tracking based on combination of a CNN and a novel growing sphere method with a population optimization, iii) intervertebral discs localization using a novel approach of spatially variant filtering of intensity profiles and iv) vertebra labeling using a CNN-based classification combined with global dynamic optimization. RESULTS: The proposed algorithm has been validated in testing databases, including also a publicly available dataset. The mean error of intervertebral discs localization is 4.4 mm, and for vertebra labeling, the average rate of correctly identified vertebrae is 87.1%, which can be considered a good result with respect to the large share of highly distorted spines and incomplete spine scans. CONCLUSIONS: The proposed framework, which combines several advanced methods including also three CNNs, works fully automatically even with incomplete spine scans and with distorted pathological cases. The achieved results allow including the presented algorithms as the first phase to the fully automated computer-aided diagnosis (CAD) system for automatic spine-bone lesion analysis in oncological patients.

• Klíčová slova
• Convolution neural network, Learning-based approach, Pathological vertebrae, Vertebra detection,
• MeSH
• algoritmy MeSH
• databáze faktografické MeSH
• diagnóza počítačová MeSH
• lidé MeSH
• metastázy nádorů MeSH
• meziobratlová ploténka diagnostické zobrazování   patologie   MeSH
• nádory kostí diagnostické zobrazování   patologie   MeSH
• nemoci páteře diagnostické zobrazování   MeSH
• neuronové sítě MeSH
• páteř diagnostické zobrazování   patologie   MeSH
• počítačová rentgenová tomografie * MeSH
• počítačové zpracování obrazu MeSH
• reprodukovatelnost výsledků MeSH
• rozpoznávání automatizované MeSH
• software MeSH
• zobrazování trojrozměrné metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

PURPOSE: Affinisol HPMC HME is a new popular form of hypromellose specifically designed for the hot melt extrusion and 3D printing of pharmaceutical products. However, reports of its thermal stability include only data obtained under inert N2 atmosphere, which is not consistent with the common pharmaceutical practice. Therefore, detailed investigation of its real-life thermal stability in air is paramount for identification of potential risks and limitations during its high-temperature processing. METHODS: In this work, the Affinisol HPMC HME 15LV powder as well as extruded filaments will be investigated by means of thermogravimetry, differential scanning calorimetry and infrared spectroscopy with respect to its thermal stability. RESULTS: The decomposition in N2 was proceeded in accordance with the literature data and manufacturer's specifications: onset at ~260°C at 0.5°C·min-1, single-step mass loss of 90-95%. However, in laboratory or industrial practice, high-temperature processing is performed in the air, where oxidation-induced degradation drastically changes. The thermogravimetric mass loss in air proceeded in three stages: ~ 5% mass loss with onset at 150°C, ~ 70% mass loss at 200°C, and ~ 15% mass loss at 380°C. Diffusion of O2 into the Affinisol material was identified as the rate-determining step. CONCLUSION: For extrusion temperatures ≥170°C, Affinisol exhibits a significant degree of degradation within the 5 min extruder retention time. Hot melt extrusion of pure Affinisol can be comfortably performed below this temperature. Utilization of plasticizers may be necessary for safe 3D printing.

• Klíčová slova
• DSC, TGA, affinisol, hot melt extrusion, thermal degradation,
• MeSH
• 3D tisk MeSH
• farmaceutická chemie * metody   MeSH
• rozpustnost MeSH
• technologie extruze tavenin * MeSH
• teplota MeSH
• vysoká teplota MeSH
• Publikační typ
• časopisecké články MeSH

The paper describes a set of approaches and routines designed to improve results in CT based 3D subtractive angiography of lower extremities via better global locally defined image data registration. Starting from the generic concept of 3D disparity-based flexible registration, modifications of this idea are made founded on prior anatomical knowledge, as segmentation into individual bone areas, their rigid registration followed by constrained flexible registration, and flexible registration of soft tissue volumes. After final subtraction, fusion of the individually derived volumes into the full volume of extremities provides the medically assessable results. The level of detail in minor vessels, and continuity of vessels including those in direct contact with the bones, have been found much better clinically than those achieved by standard contemporary commercial software.

• MeSH
• algoritmy MeSH
• artefakty * MeSH
• biologické modely MeSH
• digitální subtrakční angiografie metody   MeSH
• lidé MeSH
• počítačová rentgenová tomografie metody   MeSH
• rentgenový obraz - interpretace počítačová metody   MeSH
• reprodukovatelnost výsledků MeSH
• rozpoznávání automatizované metody   MeSH
• senzitivita a specificita MeSH
• subtrakční technika MeSH
• vylepšení rentgenového snímku metody   MeSH
• zobrazování trojrozměrné metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH
• práce podpořená grantem MeSH

Reliable 3D detection of diffraction-limited spots in fluorescence microscopy images is an important task in subcellular observation. Generally, fluorescence microscopy images are heavily degraded by noise and non-specifically stained background, making reliable detection a challenging task. In this work, we have studied the performance and parameter sensitivity of eight recent methods for 3D spot detection. The study is based on both 3D synthetic image data and 3D real confocal microscopy images. The synthetic images were generated using a simulator modeling the complete imaging setup, including the optical path as well as the image acquisition process. We studied the detection performance and parameter sensitivity under different noise levels and under the influence of uneven background signal. To evaluate the parameter sensitivity, we propose a novel measure based on the gradient magnitude of the F1 score. We measured the success rate of the individual methods for different types of the image data and found that the type of image degradation is an important factor. Using the F1 score and the newly proposed sensitivity measure, we found that the parameter sensitivity is not necessarily proportional to the success rate of a method. This also provided an explanation why the best performing method for synthetic data was outperformed by other methods when applied to the real microscopy images. On the basis of the results obtained, we conclude with the recommendation of the HDome method for data with relatively low variations in quality, or the Sorokin method for image sets in which the quality varies more. We also provide alternative recommendations for high-quality images, and for situations in which detailed parameter tuning might be deemed expensive.

• Klíčová slova
• 3D imaging, diffraction-limited spot detection, fluorescence microscopy, parameter sensitivity,
• MeSH
• algoritmy MeSH
• fluorescenční mikroskopie metody   MeSH
• konfokální mikroskopie metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• senzitivita a specificita MeSH
• zobrazování trojrozměrné metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces - The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests: I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4%-91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.

• Klíčová slova
• 3D facial models, Age estimation, Age verification, FIDENTIS database, Random forests,
• MeSH
• anatomická značka * MeSH
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• obličej anatomie a histologie   MeSH
• počítačové zpracování obrazu MeSH
• průřezové studie MeSH
• strojové učení * MeSH
• určení kostního věku metody   MeSH
• zobrazování trojrozměrné * MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Micro (micro-) axial tomography is a challenging technique in microscopy which improves quantitative imaging especially in cytogenetic applications by means of defined sample rotation under the microscope objective. The advantage of micro-axial tomography is an effective improvement of the precision of distance measurements between point-like objects. Under certain circumstances, the effective (3D) resolution can be improved by optimized acquisition depending on subsequent, multi-perspective image recording of the same objects followed by reconstruction methods. This requires, however, a very precise alignment of the tilted views. We present a novel feature-based image alignment method with a precision better than the full width at half maximum of the point spread function. The features are the positions (centres of gravity) of all fluorescent objects observed in the images (e.g. cell nuclei, fluorescent signals inside cell nuclei, fluorescent beads, etc.). Thus, real alignment precision depends on the localization precision of these objects. The method automatically determines the corresponding objects in subsequently tilted perspectives using a weighted bipartite graph. The optimum transformation function is computed in a least squares manner based on the coordinates of the centres of gravity of the matched objects. The theoretically feasible precision of the method was calculated using computer-generated data and confirmed by tests on real image series obtained from data sets of 200 nm fluorescent nano-particles. The advantages of the proposed algorithm are its speed and accuracy, which means that if enough objects are included, the real alignment precision is better than the axial localization precision of a single object. The alignment precision can be assessed directly from the algorithm's output. Thus, the method can be applied not only for image alignment and object matching in tilted view series in order to reconstruct (3D) images, but also to validate the experimental performance (e.g. mechanical precision of the tilting). In practice, the key application of the method is an improvement of the effective spatial (3D) resolution, because the well-known spatial anisotropy in light microscopy can be overcome. This allows more precise distance measurements between point-like objects.

• MeSH
• matematika MeSH
• počítačové zpracování obrazu MeSH
• referenční hodnoty MeSH
• tomografie metody   normy   MeSH
• zobrazování trojrozměrné přístrojové vybavení   metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, U.S. Gov't, P.H.S. MeSH