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FP7 Partner offer profile

Kursk State Technical University - OPTOELECTRONIC NONINVASIVE VISION SYSTEM FOR DEEP VEIN THROMBOSIS DIAGNOSTICS

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Date of filling in 05.12.2007
Organization name Kursk State Technical University
Organization adress 50 let Oktyabrya St., 94, Kursk-40, 305040
Department/Unit Chair of Computing Technique
Contact person Titov Vitaliy, DSc, Professor, Head of Chair
Phone +7-4712-587105
Fax +7-4712-587112
E-Mail titov@vt.kstu.kursk.ru
tmi@pub.sovtest.ru
Web-site http://www.kstu.kursk.ru
Organization type
  • Research
  • Education
Special Programme
Theme
Health
Call identifier
Topic number OPTOELECTRONIC NONINVASIVE VISION SYSTEM FOR DEEP VEIN THROMBOSIS DIAGNOSTICS
Call Deadline
Short description of the organization (max 12 lines): -
Expertise offered Nowadays automated diagnostic systems come in wide use in different fields of medicine. These systems allow to decrease time period required for diagnostics, to reduce diagnosis subjectivity, to reduce complexity of diagnosis statement process. The suggested optoelectronic deep vein thrombosis diagnostic method provides noninvasive screening diagnostics of lower extremities deep vein thrombosis on early stage of disease evolution. The developed method is based on shank images obtainment from different angles of view in free state and after surface veins cross-clamping by a compression cuff, shank three-dimensional surface reconstruction by comparing the identical shank points on different images, three-dimensional shank points coordinates computation, three-dimensional surface creation using the elementary triangles approximation, shank volume computation before and after surface veins cross-clamping by summation the volumes of elementary tetrahedrons. The researches are based on 3 patents of Russian Federation.
Problems to be solved and results: The proposed deep vein thrombosis diagnostic allows to:
  • perform diagnostics of lower extremities deep vein thrombosis on early stage of disease evolution with greater reliability comparing to the existing methods;
  • lower diagnostic hardware that will be at 8-12 times lower then the existing analogues;
  • render automatic diagnostic process and lower it’s complexity that allows low qualified medical staff to reform diagnostics.
Scientific keywords Machine vision image processing deep vein thrombosis diagnostics fussy logic predictive illness
Publications on the topic (other references) -
Description of previous and present experience in International Cooperation -
Previous participation in EU’s Framework Programme projects