CARTOMERGE Image Integration Module,Objectives,To become familiar with importing images (CT or MRI) into the Carto System To segment an imported image To register a segmented image to a Carto XP map,Image Acquisition,Computerized Tomography (CT),Computed Tomography(CT),Produced by a combination of X-rays, computers and detectors The X-ray tube in the housing of the scanner emits beams of x-rays through each anatomic slice of the patient The x-rays strike detectors (instead of film) and is converted via computers into cross sectional images These cross sections are stacked and become the raw data set Majority of CARTOMerge procedures done with CT,Magnetic Resonance Imaging (MRI),Magnetic Resonance Imaging -MRI,MRI produces images based upon the magnetic properties of hydrogen protons in different body tissues There are many hydrogen atoms in fat, so fat will be bright. Bone has very little hydrogen, so it will be black. Cardiac tissue is somewhere in between MRI can detect subtle changes in soft tissue with better contrast than CT No radiation. No contrast media side effects.,Image Processing,Acquired 2D slices are stacked and represented as pixels,2D slices are rendered into a 3D volume represented as voxels,Import,Radiology,Edit,The area of interest is segmented out from the rest of the anatomy,Anatomy can be segmented further and the endocardial surface is transformed into a 3D mesh.,MRI: 1.5T to 3.0T CT: 1, 8, 16, VCT,CARTOTM XP System,CARTOTM XP System,Scanners and Workstations,All scanners and workstations have their own segmentation protocols Some of these machines are configured to output their segmentation sessions, resulting in CARTOs ability to read their data. Examples are: Secondary/Reformatted DICOM3 series OR 3D Model,Requirements for CT,Within 24 hours Cardiac gating NSR:70-80% percent of R-R interval AF: On QRS wave Use beta-blockers, HR =70bpm Breathe smoothly, hold at end expiration CT: 16 above, MRI:1.5T above Use contrast ,acquire in LA phase DICOM 3 format Consistent data,Image reconstruction other than CARTO XP,Great variety of CT/MR workstations Raw data exported is usually consistent with CARTO Inconsistent data may result from: -editing (reconstructing) -viewers -scout programs -improper image sequence -missing slices -not DICOM 3 format,Importing,Select Image Processing,Opens the segmentation application,Import Image,Import by clicking the file menu, then Import Images Or in the Image Processing Screen, click the Import icon Or click Import Images directly from File Manager Menu,OR,Import Images Screen Appears,Data type appears (Raw, Segmented, or 3-D Model) Click Scan,Selecting Study,For this patient, the selected study is the largest, and the only “Consistent” one,Opening the Image Study,The imported study can be opened immediately, via the Destination panel Select the “Default” Study May also be opened from the File “open” dropdown menu or from the open icon in the Image Processing screen,Opening the Image Study,Review Image Importing Exercise Study already imported with practice Segmentation CT and Carto XP Registration Study,Segmentation,The Segmentation Process,Imported volume appears,The Segmentation Process,Rotate the volume inferiorly +/- 45 degrees,The Segmentation Process,Activate slice tools,The Segmentation Process,Bring the slice tools plane to the level of the LA,Setting the Threshold Intensity,The Intensity value determines what to mark red. Dark green indicates density range to include in the segmentation. Light green is excluded.,The Segmentation Process,Adjust the intensity level,The Segmentation Process,Adjust the intensity level: smaller increments,The Segmentation Process,Adjust the intensity level: larger increments,The Segmentation Process,Adjust the intensity level: too much intensity,The Segmentation Process,Adjust the intensity level: too little intensity,The Segmentation Process,Adjust the intensity level: just right,The Segmentation Process,Click on image when intensity appropriate Click on image to extract red areas,The Segmentation Process,Alternate view is superior view,The Segmentation Process,In superior view sternum, ribs, and aorta can be removed,The Segmentation Process,Red is extracted in the same way by clicking on the image,About the Region Grow Algorithm,The “region grow” algorithm searches for all voxels (3-D boxes) within the same Hounsfield Unit (density) threshold and adjacent to the selection, and then extracts a 3D volume based only on that data It is applied to initially extract a region of interest (ROI),The Segmentation Process,Extracted areas (ROI) will turn grey: slice tools on,The Segmentation Process,Extracted areas (ROI) will turn grey: slice tools off,Segmenting Chambers & Structures,Must now segment into separate chambers and structures Done by applying “seeds” to each chamber and structure Special “Competitive Region Grow” algorithm is applied from each seed Further differentiat