Medical image 3D visualization is one of the fundamental processes in medical diagnostics. Using the acquired 3D images it is possible to find the volume of pathology zone, which is the evidence of a specific disease. As a consequence, two problems emerge: visualization of 3D medical images and pathology zone extraction from acquired images.
Available imaging software in some cases provides the construction of 3D images based upon various medical data obtained by computer tomography, magnetic resonance imaging, scintigraphy, etc. But further processing of these images (image segmentation, pathology zone extraction) can result in loss of information during initial image reconstruction. Furthermore, existing medical imaging software does not provide the automatic extraction of regions of interest. As a consequence, often pathology zone volumes are calculated manually and that results in lack of precision.
In this work methods for solving these problems are proposed. This work describes an approach of 3D model reconstruction from medical images by using detailed initial information obtained for forming DICOM files. For extraction of pathology zones and volume estimation an automatic procedure of region calculation is proposed. The described methods can provide practical improvements to the reliability of medical diagnostics.
- Medical images
- volume estimation
- pathology zone
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Dastidar P, Heinonen T, Vahvelainen T, Elovaara I, Eskola H (1999) Computerised volumetric analysis of lesions in multiple sclerosis using new semi-automatic segmentation software. Med. Biol. Eng.Comput., vol. 37, 1999, pp 104–107
Jiang C, Jiang L, Zhang X, Gevantmakher M, Meinel C (2004) A New Practical Tool for 3D Medical Image Segmentation, Visualization and Measurement. Proceedings of CCCT, 2004, Austin, USA
Smitha S, Revathy K, Kesavadas C (2006) Segmentation and Volume Estimation of Brain tissues from MR Images. IMECS, 2006, pp 543–547
Krechetova K, Glaz A (2007) Development of a new segmentation method for medical images. Biomed. Eng. conference proc., Kaunas, Lithuania, 2007, pp 133–136
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Krechetova, K., Glaz, A., Platkajis, A. (2008). 3D Medical Image Visualization and Volume Estimation of Pathology Zones. In: Katashev, A., Dekhtyar, Y., Spigulis, J. (eds) 14th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. IFMBE Proceedings, vol 20. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69367-3_142
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69366-6
Online ISBN: 978-3-540-69367-3