USING INFORMATION TECHNOLOGIES FOR ANALYSIS OF LUNG PATHOLOGIES BY MEANS OF X-RAY COMPUTED TOMOGRAPHY
Anodina-Andrievskaya Elena Mikhailovna
Saint Petersburg National Research University of Information Technologies, Mechanics and Optics
Abstract. The article touches on the problems of identifying oncologic diseases among population. The author makes a comparison of various types of tomographical diagnostics, such as: magnetic resonance imaging, positron-emission tomography, X-ray computed tomography. The researcher analyzes the possibilities of their use for the identification of lung pathologies, justifies requirements for the special software of the system for the identification of oncologic pathologies.
Key words and phrases: онкологические заболевания, компьютерная томография, обработка изображений, информационные технологии, интерактивные компьютерные алгоритмы, oncologic diseases, computed tomography, image processing, information technologies, interactive computer algorithms
Open the whole article in PDF format. Free PDF-files viewer can be downloaded .
References:
Galaidin P. A., Ivanov V. A., Marusina M. Ya. Raschet i proektirovanie elektromagnitnykh sistem magnitorezonansnykh tomografov: uchebnoe posobie. SPb.: SPbGU ITMO, 2004. 87 s.
Ivanov V. A., Marusina M. Ya. Primenenie teorii grupp pri reshenii zadach realizatsii izmeritel'nykh preobrazovanii // Izvestiya vuzov. Priborostroenie. 2000. T. 43. № 6. S. 36-39.
Ivanov V. A., Marusina M. Ya., Sizikov V. S. Obrabotka izmeritel'noi informatsii v usloviyakh neopredelennostei // Kontrol'. Diagnostika. 2001. № 4. S. 40-43.
Ivanov V. A., Marusina M. Ya., Flegontov A. V. Invariantnye approksimatsii i ikh primenenie v MR-tomografii // Nauchnoe priborostroenie. 2003. T. 13. № 2. S. 22-26.
Lorigan P. Rak legkogo. M.: Prakticheskaya meditsina, 2009. 196 s.
Magonov E. P., Trofimova T. N. Avtomaticheskaya segmentatsiya MRT-izobrazhenii golovnogo mozga: metody i programmnoe obespechenie // Institut mozga cheloveka im. N. P. Bekhterevoi Rossiiskoi akademii nauk. Lektsii i obzory. 2012. T. 3. № 3. S. 35-40.
Marusina M. Ya. Invariantnyi analiz i sintez v modelyakh s simmetriyami. SPb.: SPbGU ITMO, 2004. 144 s.
Marusina M. Ya. Korrektsiya neodnorodnosti osnovnogo magnitnogo polya MR-tomografa na postoyannykh magnitakh: diss. … k.t.n. SPb.: ITMO, 1993. 128 s.
Marusina M. Ya. Metody povysheniya kachestva tomograficheskikh izobrazhenii na osnove invariantnogo analiza i sinteza // Izvestiya vuzov. Priborostroenie. 2005. T. 48. № 5. S. 29-33.
Marusina M. Ya. Optimizatsiya izmeritel'nykh preobrazovanii na osnove teoretiko-gruppovogo analiza // Izvestiya vuzov. Priborostroenie. 2005. T. 48. № 3. S. 27-31.
Marusina M. Ya. Povyshenie kachestva izmerenii na osnove teoretiko-gruppovogo analiza i sinteza izmeritel'nykh sistem: diss. … d.t.n. SPb., 2005. 340 s.
Marusina M. Ya., Kaznacheeva A. O. Sovremennye vidy tomografii. SPb.: SPbGU ITMO, 2006. 151 s.
Trakhtenberg A. Kh., Chissov V. I. Klinicheskaya onkopul'monologiya. M., 2000. 599 s.
Chissov V. I., Starinskii V. V., Petrova G. V. Zlokachestvennye obrazovaniya v Rossii v 2011 godu. M.: FGBU "MNIOI im. P. A. Gertsena" Minzdrava Rossii, 2013. 289 s.
Alilou M., Kovalev V., Snezhko E., Taimouri V. A Comprehensive Framework for Automatic Detection of Pulmonary Nodules in Lung CT Images // Image Analysis and Stereology. 2014. Vol. 33. № 1. P. 13-27.
Desai S. Lung Cancer. Cambridge University Press, 2007.
Dhawan A. P. Medical Image Analysis. Second edition. IEE Press, 2011. 380 p.
Dougherty G. Digital Image Processing for Medical Applications. Cambridge University Press, 2009. 447 p.
Русский
