COMSATS Institute of Information Technology, Islamabad PAKISTAN A MATLAB BASED INTERACTIVE GRAPHICAL USER INTERFACE FOR ADVANCE IMAGE RECONSTRUCTION ALGORITHMS IN MRI Medical Image Processing Research Group Ver. 2015 THE STEP BY STEP INTERACTIVE GUIDE O p e n S o u r c e A v a i l a b l e a t h t t p : / / w w 3. c o m s a t s. e d u. p k / m i p r g / d o w n l o a d s
WELCOME TO FOR A MATLAB BASED INTERACTIVE GRAPHICAL USER INTERFACE FOR ADVANCE IMAGE RECONSTRUCTION ALGORITHMS IN MRI P a g e 1
The Graphical User Interface (GUI) is developed to reconstruct Magnetic Resonance Imaging (MRI) data using various advance algorithms. These algorithms include SENSE, Compressed Sensing, Conjugate Gradient Sense along with the Geometry-factor calculations and family of Radial GRAPPA. This MATLAB (R2013a) based GUI environment is a multiple window interface. The GUI provides the researchers, medical practitioners an easy and interactive tool to test their data using various advanced reconstruction algorithms in MRI. Sampled human head images acquired using 1.5 and 3 Tesla MRI scanners. Use <title_page.fig> to start the GUI interface (e.g., like smap1(t2).mat>,<smap1(t3).mat>, <smap1(t4).mat>,<smap1(t5).mat>) P a g e 1
The Reconstruction Methods i.e, SENSE, Compressed Sensing, Conjugate Gradient Sense, Family of Radial GRAPPA, g-factor Calculations, are listed here for your Selection Use Help Menu P a g e 2
STEP 1: SENSITIVITY ENCODING Fully-sampled/Undersampled data loading for SENSE Reconstruction On selecting SENSE algorithm Question Window appears asking User is your data under-sampled? Note: (If your data is not undersampled then select No on Question window) P a g e 3
STEP 2: SENSE RECONSTRUCTION WITH UNDERSAMPLED DATA If Yes then Load under-sampled Image (e.g. aliased_imaget3), Choose acceleration factor e.g.1, 2, 3 etc. Select Sensitivity Map (e.g. new_smap1) and Reconstruct your data P a g e 4
STEP 3: SENSE RECONSTRUCTION IF FULLY SAMPLED DATA IS AVAILABLE Select Image for SENSE Reconstruction Using Fully-Sampled MRI Data Set <smap1(t2).mat>,<smap1(t3).mat> (1.5 Tesla) <smap1(t4).mat>,<smap1(t5).mat> (3.0 Tesla) Enter which coil image you would like to visualize e.g. 1, 2, 3 etc. If you want to reconstruct it then proceed to reconstruction by pressing <Next> button P a g e 5
STEP 4: UNDER-SAMPLING AND RECONSTRUCTION FOR SELECTED SAMPLED MRI DATA SET (1.5T) At SENSTIVITY ENCODING window Select acceleration factor e.g.1, 2, 3 etc. Then Select Sensitivity Map <new_smap(t3).mat> Select Row/Column Under-sampling Reconstruction and press <RUN> button P a g e 6
After the algorithm process completion press <Display> button for the following results P a g e 7
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STEP 5: COMPRESSED SENSING Select Reconstruction algorithm from the main menu window <Compressed Sensing> P a g e 9
STEP 6: LOADING FULLY SAMPLED DATA SET Select data e.g. fully-sampled data (<smap1(t2).mat> 256x256x8), Enter number of coil for visualization e.g. 1, 2, 3 etc (optional). After loading the data set you can proceed to reconstruction using <Next> button P a g e 10
STEP 6: IMAGE RECONSTRUCTION THROUGH COMPRESSED SENSING ALGORITHM Enter acceleration factor e.g. 1, 2, 3 etc. Select trajectories e.g. VD-Cartesian, Radial or Spiral then press <Reconstruction> button to start processing and <Display> for results visualization P a g e 11
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Use Back for MAIN MENU. P a g e 13
STEP 7: CG-SENSE Select Reconstruction Algorithm: Conjugate Gradient Sense P a g e 14
STEP 8: UNDERSAMPLED IMAGE RECONSTRUTION THROUGH CG SENSE If your data is under-sampled then Load Undersampled Data e.g. <aliased(t3).mat>, Load Coil Sensitivity e.g. <new_smap(t3)>, Load Trajectory e.g. (either radial or spiral <k_radial_traj_p_384.mat>) and then Press <Run> button for Reconstruction (Note: If data is not under-sampled then proceed to next Step) P a g e 15
STEP 9: FULLY SAMPLED IMAGE RECONSTRUCTION THROUGH CG SENSE Select fully sampled data by pressing Browse button e.g. <smap1 (T3).mat> (Optional) Enter the number of coil for visualization then Press <Display> for visualization Press <Next> to proceed reconstruction P a g e 16
Enter No. of Iterations e.g. (15, 20 etc.), acceleration factor e.g. 2, 3, 4 etc. and select Sensitivity <new_smap(t3).mat>. Select trajectory e.g. Spiral or Radial <k_radial_traj_p_384.mat> then press <Reconstruct> and <Display> button for the results visualization P a g e 17
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STEP 10: FAMILY OF RADIAL GRAPPA ALGORITHMS Select GRAPPA Reconstruction method and enter the reconstruction parameters then press <Reconstruct> button to process the results for visualization P a g e 19
STEP 10: G-FACTOR MAP If receiver coils sensitivity maps are available press <yes> button P a g e 20
Load Sensitivity Maps e.g. <new_smap(t3).mat>, enter acceleration Factor e.g. 2, 3, etc. Calculate g- Factor e.g. Row-wise or Column-wise P a g e 21
STEP 10: SENSITIVITY MAP ESTIMATION If receiver coils sensitivity maps are not available then load low resolution image e.g. <aliased(t3).mat> Enter the number of coils then press <RUN> button to estimate the sensitivity maps and press <Next> button to proceed on next step P a g e 22
STEP 10: G-FACTOR CALCULATIONS On Pressing Next (Sensitivity Map Estimation Window) a warning window appears alarming the user that sensitivity map is already estimated in previous step P a g e 23
Load Low resolution Image e.g. <smap1 (T3)>, Calculate Sensitivity Map e.g. 2, 3, etc. then press <Run> button P a g e 24
A MATLAB BASED INTERACTIVE GRAPHICAL USER INTERFACE FOR ADVANCE IMAGE RECONSTRUCTION ALGORITHMS IN MRI P a g e 25
TROUBLESHOOTING In case of any problem regarding GUI feel free to contact: a.raza@comsats.edu.pk abbasrazav4s@gmail.com arsalanahmed639@hotmail.com mudi.abbasi@hotmail.com yasirtariq050@hotmail.com hammad.omer@comsats.edu.pk P a g e 26