Nowadays the multi-layer computed tomography (CT) shots with contrast dye used for detection of small pathological growths regions are widely spread in medical clinics. Although, CT study with contrast dye use has contraindications and is much more expensive for patients than study without use of dye. This article proposes the algorithm based on segmentation of three-dimensional signal received from CT (without dye use). The algorithm allows to identify a pathological growths automatically and to detect studying object regions with the help of 3D graph model based on received data. Algorithm also evaluates parameters of small objects and sinuses, which occupy only small part of initial CT layers, with high accuracy.
Nowadays the multilayer computed tomography shots with contrast dye used for detection of small pathological growth are widespread in medical clinics. Although, tomography study with contrast dye use has contraindications and is much more expensive for patients than study without use of dye. This article proposes data processing method based on segmentation of multilayer computed tomography shots without use of dye. The method allows to automatically identify pathological growths and to detect studying object areas. The software, developed according to this method, evaluates parameters of small objects and sinuses, which occupy only small part of initial computed tomography layers, with high accuracy.
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