technische universiteit eindhoven /department of biomedical engineering Segmentation Techniques for the Visible mouse By Virjanand Panday Supervisor: B.M. ter Haar Romeny Date: 4 June 2003

technische universiteit eindhoven /department of biomedical engineering The Visible Mouse Project Magnetic Resonance Lab 3D database of the mouse Develop non-invasive diagnostic routines for humans

technische universiteit eindhoven /department of biomedical engineering Comparable to The Visible Human Fast overview of organs and possible anomalies For 3D rendering organs must first be detected from surrounding tissue

technische universiteit eindhoven /department of biomedical engineering Example: Detection Kidney Weak edge Structures inside Strong edges surrounding

technische universiteit eindhoven /department of biomedical engineering Definition of Problem Investigate segmentation techniques for the visible mouse

technische universiteit eindhoven /department of biomedical engineering Overview of Presentation Introduction Overview Segmentation Techniques Watershed Segmentation Active Contours Segmentation Levelset Snake Some Results Discussion

technische universiteit eindhoven /department of biomedical engineering Classification Segmentation Techniques Region Based: Homogeneities Region Growing Edge Based Inhomogeneities LoG, Sobel operators Graph Searching or dynamic programming Classification: Multiple values Clusters Minimum distance to means or artificial neural networks

technische universiteit eindhoven /department of biomedical engineering Used Segmentation Techniques Watershed (uses region and edge based techniques) Active Contours (geometric reasoning)

technische universiteit eindhoven /department of biomedical engineering Watershed: Theory Image as landscape Dam construction Plaatje van landscapeplaatje van sinus dam

technische universiteit eindhoven /department of biomedical engineering Watershed: Nabla Vision

technische universiteit eindhoven /department of biomedical engineering Active Contours Forces derived from the curve itself ( Curvature, Size surface enclosed, etc. ) Forces derived from image ( Gradient, Texture, etc. ) Other Forces ( Balloon force ) Plaatje van random contour op muis beeld

technische universiteit eindhoven /department of biomedical engineering Levelset: Evolution Function Plaatje van cone distance function

technische universiteit eindhoven /department of biomedical engineering Levelset: Flow Function F Constant: F=  Curvature: F=- 

technische universiteit eindhoven /department of biomedical engineering Levelset: Stopping Terms Filmpje curve met stop term Plaatje stopping term

technische universiteit eindhoven /department of biomedical engineering Snake: Evolution Equation

technische universiteit eindhoven /department of biomedical engineering Comparing Results

technische universiteit eindhoven /department of biomedical engineering Results Visualized in 3D Multiple slices

technische universiteit eindhoven /department of biomedical engineering Discussion and Future Work Watershed needs postprocessing, but automatic Levelset requires strong edges ( Stronger attraction towards edges ), but addapts very well to topology of image Snake stays one contour, but spans gaps in edges well 3D looks smoother if methods applied directly on 3D: for levelset easy with 4D function, for snake a lot of bookkeeping of the surface points Better testing of correctness segmentation

technische universiteit eindhoven /department of biomedical engineering Acknowledgements Bart ter Haar Romeny Aurelie Bugeau Markus van Almsick Anna Vilanova Bartroli Arnold Schilham Gustav Strijker and Willem Mulder Paul van den Bosch