Tomographic Imaging

Magnetic resonance scanner in hospital
Course given by
Prof. Dr.-Ing. Georg Schmitz
Course number
141223
Language
German
Credit Points
5
Hours per week
4
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Moodle

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Contents

Using to­mo­gra­phic ima­ging tech­ni­ques, image sli­ces of tis­sue and bone struc­tu­res can be re­con­struc­ted from pro­jec­tions, i.e. from me­a­su­red, in­te­gral re­la­ti­ons­hips of phy­si­cal pa­ra­me­ters. Com­pu­ter to­mo­gra­phy (CT) me­a­su­res the pe­ne­tra­ti­on of X-rays through a vo­lu­me to be ima­ged at dif­fe­rent angles and re­con­structs the X-ray at­te­nua­ti­on co­ef­fi­ci­ent. Ma­gne­tic re­so­nan­ce to­mo­gra­phy (MR), on the other hand, uses nu­cle­ar ma­gne­tic re­so­nan­ce ef­fects and ima­ges pro­ton den­si­ties weigh­ted by re­la­xa­ti­on times. From the phy­si­cal and ma­the­ma­ti­cal ba­sics to prac­tical­ly im­portant re­con­struc­tion pro­ce­du­res, all steps from data ac­qui­si­ti­on to the image are taught.

Lectures

Room
ID 04/445
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Lesson begins
08:15
Lesson ends
09:45
First lesson is on
Wednesday, 10.04.2024

Excercises

Room
ID 04/445
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Excercise begins
10:15
Excercise ends
11:45
First excercise is on
Wednesday, 17.04.2024

Exam

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Type of exam
Oral exam
Exam date
Individual Appointment
Duration of exam
30 minutes
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Registration for the exam
FlexNow
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Objectives

After suc­cess­ful com­ple­ti­on of the mo­du­le, stu­dents have know­ledge of the most im­portant to­mo­gra­phic dia­gnostic ima­ging pro­ce­du­res (X-ray com­pu­ted to­mo­gra­phy, ma­gne­tic re­so­nan­ce ima­ging). They know the basic tech­ni­cal com­po­n­ents of the ima­ging sys­tems under con­s­i­de­ra­ti­on and can ex­plain how they work. They un­der­stand the basic phy­si­cal ef­fects (e.g. X-ray at­te­nua­ti­on, nu­cle­ar ma­gne­tic re­so­nan­ce) and can di­s­cuss them. Stu­dents un­der­stand the theo­ry of to­mo­gra­phic re­con­struc­tion (Fou­rier-Sli­ce-Theo­rem, Fou­rier-Dif­frac­tion Theo­rem) and can de­ri­ve and ex­plain the struc­tu­re and the achie­ved image qua­li­ty of the dif­fe­rent sys­tems. They are able to im­ple­ment known al­go­rith­ms for image re­con­struc­tion and in­de­pen­dent­ly de­ve­lop and eva­lua­te new al­go­rith­ms. Through the ex­er­ci­ses in small groups, part­ly on com­pu­ters, the stu­dents are able to apply what they have le­ar­ned in a small team. They are able to ex­plain their so­lu­ti­ons and to pre­sent sup­porting ar­gu­ments.
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Requirements

none

Prior knowledge

Know­ledge of sys­tem theo­ry, Fou­rier trans­for­ma­ti­on and si­gnal pro­ces­sing, cor­re­spon­ding to those taught as ba­sics in the lec­tu­res of the ba­che­lor's pro­gram in Elec­tri­cal En­gi­nee­ring and In­for­ma­ti­on Tech­no­lo­gy.

Literature

  1. Mor­ne­burg, Heinz “Bild­ge­ben­de Sys­te­me für die me­di­zi­ni­sche Dia­gnos­tik”, Pu­bli­cis Cor­po­ra­te Pu­blis­hing, 1995
  2. Buzug, Thors­ten M. “Ein­füh­rung in die Com­pu­ter­to­mo­gra­phie. Ma­the­ma­tisch-phy­si­ka­li­sche Grund­la­gen der Bild­re­kon­struk­ti­on”, Sprin­ger, 2007
  3. den Boer, Jac­ques A., Vlaar­din­ger­bro­ek, Ma­ri­us T. “Ma­gne­tic Re­so­nan­ce Ima­ging. Theo­ry and Prac­tice”, Sprin­ger, 2003
  4. Kak, Avi­nash C., Sla­ney, Mal­colm “Prin­ci­ples of Com­pu­te­ri­zed To­mo­gra­phic Ima­ging”, I.​E.​E.​E.​Press, 1989
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Miscellaneous

Re­gis­tra­ti­on is car­ried out via the E-Le­arning Por­tal Mood­le of the Ruhr-Uni­ver­si­tät Bo­chum. The re­qui­red in­for­ma­ti­on is pro­vi­ded in the first lec­tu­re.