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Successes and Challenges in Effectors and Scanner Control. Nobuhiko Hata, PhD Brigham and Women’s Hospital. Issues. Basic functions for Image Guided Therapy (visualization, image I/O, patient-to-image registration) are relatively easy to implement (thanks to VTK and ITK)
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Successes and Challenges in Effectors and Scanner Control Nobuhiko Hata, PhD Brigham and Women’s Hospital
Issues • Basic functions for Image Guided Therapy (visualization, image I/O, patient-to-image registration) are relatively easy to implement (thanks to VTK and ITK) • Challenge 1: Develop and apply new medical image processing methods to enable new therapy options • Challenge 2: Provide meeting point for robotics, medical image processing, and bio-physics
Objective • Open source software 3D Slicer • Modular architecture for multiple IGT applications • Integration to FDA-approved commercial systems • Issues
Slicer • 1996: Carl-Fredrick Westin (newly hired post-doc) and Noby Hata (SPL grad student) developed prototype using VTK-beta • 1997: First MR-guided neurosurgery • Dave Gering (MIT grad student) re-design the software • Lauren O'Donnell (1999-), Steve Pieper (2001-) • Pis: Ron Kikinis, Ferenc Jolesz, Eric Grimson, William Wells III
Multiple applications • Software design to maximize function commonalities among applications • Brain (biopsy, craniotomy, NdYAG laser ablation) • Prostate (brachytherapy, biopsy) • Liver and kidney (Microwave, laser ablation) • Endoscopy (neuroendoscopy)
DICOM image transfer Visualization Navigation Image registration Neurosurgery
“Multi-modality” MRIg Surgery Registration is the key-enabling technology
MR-guided Liver ablation Therapy ACADEMIC RADIOLOGY 10 (12): 1442-1449 DEC 2003
MRI-guided Thermal Therapy • Image display • DICOM transfer • Thermal mapping (modifying fMRI module) Comput Med Imaging Graph
MRI-guided prostate therapy DICOM image transfer Rigid and non-rigid image registration Planning Scanner control Radiology 220(1), 263-268, 2001
Slicer with Hitachi scanner DICOM image transfer Patient-to-image registration Navigation Tumor segmentation for resection monitoring
Pituitary tumor in horizontal open-MRI 3D Slicer (Freeware) Navigation tool for image-guided therapy
Intraoperative Tumor Segmentation • ITK-VTK-Slicer • Fuzzy connectivity • 30+ cases at 0.3T Hitachi Horizontal gap scanner Hata N, Muragaki Y, Inomata T, Maruyama T, Iseki H, Hori T, Dohi T. Intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery for tumor resection rate control. Acad Radiol. 2005;12(1):116-22.
3D Slicer Segmentation Pre-Op to Intra-Op image registration Navigation Toshiba navigation (pre-commercial) TCP/IP peer-to-peer connection Patient-to-image registration result Tracking data Linking commercial navigation and research software
Slicer for Surgical Robot Robot as tracking device
System Integration to Signa/SP • Off-the-shelf system + 3D Slicer MRT Workstation TPS BIT-3 Image Transfer 0.5fps Image Transfer 0.5fps Slicer 10 Mbps
System Integration to Signa/SP • (Pre-) MR Slicer MRT Workstation TPS BIT-3 Echo transfer 128fps Echo Transfer 128fps Slier Image Transfer 32fps Recon 100 Mbps
GE Medical Systems Signa Horizon LX System • Host • SGI Workstation / MIPS Based Processor • IRIS Operating System (SGI) • Transceiver, Processing and Storage (TPS) • VME / Motorola Based Processor • VxWorks (Wind River) Scanner TPS Host
Reconstruction WS • CPU: Intel Pentium4 2.8 GHz (i850 Chipset) • Memory: 512MB (PC1066 RIMM) • Graphics: nVIDIA GeForce4 MX440 • OS: RedHat Linux 7.3, Kernel 2.4.18 with nVIDIA Graphics Driver • Software • Real-time display of echo and k-space • Real-time image reconstruction • Navigator-echo based matching • Host control
Pre-operative Diagnostic Imaging Intra-operative imaging IGT software as an integration platform Image Processing Image Processing Navigation Navigation Registration Tracking probe Observation Robot Action Physician Treatment Patient
Issues • Basic functions for Image Guided Therapy (visualization, image I/O, patient-to-image registration) are relatively easy to implement (thanks to VTK and ITK) • Challenge 1: Develop and apply medical image processing technology to enable new therapy options • Challenge 2: Provide meeting point for robotics, medical image processing, and bio-physics • Do not think IGT software as free navigation system • Think IGT software as an integration platform TO ENABLE NEW THERAPY