Nasal breathing is essential for respiratory function, influenced by the complex anatomy of the nasal cavity, which conditions the inhaled air by heating, cleansing and humidifying it. Disorders such as nasal obstruction or nasal septal deformities can lead to sinusitis, decreased sense of smell and sleep apnea. Septoplasty corrects these problems, but requires postoperative splinting. This study focuses on the development of personalized intranasal splints using advanced CT image processing. The software analyzes DICOM images, identifies septal distortions and calculates geometric parameters to create personalized splints. These silicone splints stabilize the nasal septum, promote airflow and enhance recovery comfort, seamlessly integrating with 3D printing technology for precise replication. This innovative approach improves surgical outcomes, providing a better quality of life for the patient after septoplasty.
Diabetes can lead to a number of serious complications, in particular, diabetic retinopathy, which occurs in patients with diabetes and can lead to vision loss. In this regard, the development of an information system for the diagnosis of diabetic retinopathy is an important task in the medical field. Such a system can greatly facilitate the diagnostic process and help doctors detect and treat diabetic retinopathy in time. As a result of the conducted research, the urgent task of increasing the accuracy of diagnosis of fundus diseases was solved by using methods of pre-processing images to improve their informative characteristics, statistical analysis and differentiation of pathologies with the help of a decision support system based on neural network technologies. A comparative analysis of the existing methods of diagnosing diabetic retinopathy and other eye diseases was carried out, according to which it is clear that intellectual analysis and pre-processing of the received images of the fundus can significantly improve the results of diagnostics, especially early screening, which is important for preventing severe stages of the disease.
KEYWORDS: Monte Carlo methods, Scattering, Detection and tracking algorithms, Signal attenuation, Absorption, Modeling, Light scattering, Visualization, Sensors, Protactinium
A method for rendering inhomogeneous volumes using perturbation functions is presented. An approach is proposed for sampling light transmission paths in heterogeneous media. At the initial stage of calculations, light transmission paths are constructed in a closed form. Then the heterogeneous component is averaged by adding a formal medium. Next, the path-tracking algorithm is used. Due to this, there is no need to calculate strict boundaries of the attenuation function. Samples in the closed-form light transmission path and the averaged medium are made separately. This minimizes the costly calculations of collision coefficients that change when traversing space.
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