MIAL

3D Live-Wire

MSc Student: Andrew Top
Principal Investigator: Ghassan Hamarneh
Principal Investigator: Rafeef Abugharbieh
Alumni: Miranda Poon

Accurate and automatic 3D medical image segmentation remains an elusive goal and manual intervention is often unavoidable. We are working on techniques that allow the user to provide minimal intuitive interaction for guiding the 3D segmentation process.

Please visit the new website TurtleSeg.org

Publications

Andrew Top, Ghassan Hamarneh, and Rafeef Abugharbieh. Active Learning for Interactive 3D Image Segmentation. In Lecture Notes in Computer Science, Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 585-592, 2011. 

Andrew Top, Ghassan Hamarneh, and Rafeef Abugharbieh. Spotlight: Automated Confidence-based User Guidance for Increasing Efficiency in Interactive 3D Image Segmentation. In Medical Image Computing and Computer-Assisted Intervention Workshop on Medical Computer Vision (MICCAI MCV), pages 1-11 pages, 2010. 

Miranda Poon, Ghassan Hamarneh, and Rafeef Abugharbieh. Efficient Interactive 3D Livewire Segmentation of Objects with Arbitrarily TopologiesComputerized Medical Imaging and Graphics, 32(8):639-650, 2008.   

Miranda Poon, Ghassan Hamarneh, and Rafeef Abugharbieh. Segmentation of Complex Objects with Non-Spherical Topologies from Volumetric Medical Images using 3D Livewire. In SPIE Medical Imaging, volume 6512-31, pages 1-10, 2007.  

Ghassan Hamarneh, Johnson Yang, Chris McIntosh, and Morgan Langille. 3D live-wire-based semi-automatic segmentation of medical images. In SPIE Medical Imaging, volume 5747, pages 1597-1603, 2005.  

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