Ústav počítačové grafiky a multimédií

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A 3D Scan Model and Thermal Image Data Fusion Algorithms for 3D Thermography in Medicine
(NEUVEDEN, 2017-11-08) Chromý, Adam; Klíma, Ondřej
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.
Mathematical model of mechanical testing of bone-implant (4.5 mm LCP) construct
(University of Veterinary and Pharmaceutical Sciences in Brno, 2012-09-17) Urbanová, Lucie; Blažek-Fialová, Iva; Srnec, Robert; Pěnčík, Jan; Kršek, Přemysl; Nečas, Alois
The study deals with the possibility of substituting time- and material-demanding mechanical testing of a bone defect fixation by mathematical modelling. Based on the mechanical model, a mathematical model of bone-implant construct stabilizing experimental segmental femoral bone defect (segmental ostectomy) in a miniature pig ex vivo model using 4.5 mm titanium LCP was created. It was subsequently computer-loaded by forces acting parallel to the long axis of the construct. By the effect of the acting forces the displacement vector sum of individual construct points occurred. The greatest displacement was noted in the end segments of the bone in close proximity to ostectomy and in the area of the empty central plate hole (without screw) at the level of the segmental bone defect. By studying the equivalent von Mises stress SIGMAeqv on LCP as part of the tested construct we found that the greatest changes of stress occur in the place of the empty central plate hole. The distribution of this strain was relatively symmetrical along both sides of the hole. The exceeding of the yield stress value and irreversible plastic deformations in this segment of LCP occurred at the acting of the force of 360 N. These findings are in line with the character of damage of the same construct loaded during its mechanic testing. We succeeded in creating a mathematical model of the bone-implant construct which may be further used for computer modelling of real loading of similar constructs chosen for fixation of bone defects in both experimental and clinical practice.
Efficient Low-Resource Compression of HIFU Data
(2018-06-26) Klepárník, Petr; Bařina, David; Zemčík, Pavel; Jaroš, Jiří
Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), important for model-based treatment planning, generate large amounts of data. Typically, it is necessary to save hundreds of gigabytes during simulation. We propose a novel algorithm for time-varying simulation data compression specialised for HIFU. Our approach is particularly focused on on-the-fly parallel data compression during simulations. The algorithm is able to compress 3D pressure time series of linear and non-linear simulations with very acceptable compression ratios and errors (over 80% of the space can be saved with an acceptable error). The proposed compression enables significant reduction of resources, such as storage space, network bandwidth, CPU time, and so forth, enabling better treatment planning using fast volume data visualisations. The paper describes the proposed method, its experimental evaluation, and comparisons to the state of the arts.
Intensity-based non overlapping area registration supporting "drop-outs" in terms of model-based radiostereometric analysis
(2018-03-28) Klíma, Ondřej; Novobilský, Petr; Madeja, Roman; Bařina, David; Chromý, Adam; Španěl, Michal; Zemčík, Pavel
A model-based radiostereometric analysis (MBRSA) is a method for precise measurement of prosthesis migration, which does not require marking the implant with tantalum beads. Instead, the prosthesis pose is typically recovered using a feature-based 2D-3D registration of its virtual model into a stereo pair of radiographs. In this study, we evaluate a novel intensity-based formulation of previously published non-overlapping area (NOA) approach. The registration is capable to perform with both binary radiographic segmentations or non segmented X-ray images. In contrast with the feature-based version, it is capable to deal with unreliable parts of prosthesis. As the straightforward formulation allows efficient acceleration using modern graphics adapters, it is possible to involve precise high-poly virtual models. Moreover, in case of binary segmentations, the non-overlapping area is simply interpretable, useful for indicating the accuracy of the registration outcome. In silico and phantom evaluations were performed using a cementless Zweymüller femoral stem and its reverse engineered (RE) model. For initial pose estimates with difference from the ground-truth limited to 4 mm and 4° respectively, the mean absolute translational error was not higher than 0.042+-0.035 mm. The error in rotation around the proximodistal axis was 0.181+-0.265°, error for remaining axes was not higher than 0.035+-0.037°.
A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers
(MDPI, 2023-05-22) Zuluaga-Gomez, Juan; Prasad, Amrutha; Nigmatulina, Iuliia; Motlíček, Petr; Kleinert, Matthias
In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken communications from ATCo trainees, and it performs automatic speech recognition and understanding. Thus, it goes beyond only transcribing the communication and can also understand its meaning. The output is subsequently sent to a response generator system, which resembles the spoken read-back that pilots give to the ATCo trainees. The overall pipeline is composed of the following submodules: (i) an automatic speech recognition (ASR) system that transforms audio into a sequence of words; (ii) a high-level air traffic control (ATC)-related entity parser that understands the transcribed voice communication; and (iii) a text-to-speech submodule that generates a spoken utterance that resembles a pilot based on the situation of the dialogue. Our system employs state-of-the-art AI-based tools such as Wav2Vec 2.0, Conformer, BERT and Tacotron models. To the best of our knowledge, this is the first work fully based on open-source ATC resources and AI tools. In addition, we develop a robust and modular system with optional submodules that can enhance the system's performance by incorporating real-time surveillance data, metadata related to exercises (such as sectors or runways), or even a deliberate read-back error to train ATCo trainees to identify them. Our ASR system can reach as low as 5.5% and 15.9% absolute word error rates (WER) on high- and low-quality ATC audio. We also demonstrate that adding surveillance data into the ASR can yield a callsign detection accuracy of more than 96%.

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