Introduction to Multilingual Retrieval Augmented Generation (RAG)
ITK Tutorial Presentation Slides-946
1. Introduction to ITK Segmentation The Insight Consortium presented by Josh Cates Scientific Computing and Imaging Institute University of Utah
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4. Big Picture: The Role of ITK Filters Raw Data Filtering linear nonlinear Feature Extraction differential geom. edge detection Segmentation region growing watersheds level-sets Visualization binary volume meshes labeled image implicit surfaces Dataflow architecture: ITK filters fit together to produce segmentation applications. Preprocessing Moral: ITK segmentation filters are not complete applications – components in a pipeline.
5. Big Picture: The Role of ITK Filters Raw Data Filtering Feature Extraction Segmentation Visualization User Interface
42. Example: Watersheds GUI Watershed Depth Threshold InsightApplications/SegmentationEditor 3D isosurface rendering Data with overlay Watershed transform Segmentation in progress Sliders manipulate watershed depth and position in the hierarchy.
48. PDE Solver Hierarchy Dense Finite Difference Solver Sparse Narrow Band Diffusion Other Solvers Finite Difference Function Diffusion Level Set Other Functions Aniso. Diff Curv. Limited Segment. Threaded Sparse 4 th Order Deformable Registration
49. Constructing a PDE Filter Input Image Output Image (Filtered) Solver Object Subclass Function Object Parameters
50. LevelSet Segmentation Framework “ Feature” Image Initial Model Output Model User-Defined LS Seg. Filter Level-Set Segmentation Filter Finite Difference Solver Curvature Function Finite Difference Solver Sparse-Field Level-Set Solver Level Set Function Shape Detection Function Active-Contours Function Laplacian Function Threshold Function Canny Edges Function
59. SNAP User Interface Dialog for setting evolution parameters Scalpel tool for editing segmentations Manual Segmentation InsightApplications/Snap SNAP Segmentation of the Caudate Nuclei SNAP Segmentation Wizard with VCR Controls
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62. Confidence Connected + LevelSet Result Initial confidence- connected result Post-processing with Canny LS segmenter LS Speed Term: distance from Canny edges Data: Warfield, Nabavi, Butz, Tuncali, Silverman, “Intraoperative segmentation and nonrigid registration for image guided therapy, in: MICCAI'2000, SpringerVerlag, 2000, pp.176-185.