ALGORITHMS FOR MULTI-MODAL REGISTRATION IN CANCER DIAGNOSIS AND IMAGING
ALGORITHMS FOR MULTI-MODAL REGISTRATION IN CANCER DIAGNOSIS AND IMAGING
批准号:
8341400
负责人:
PHILIPP J. STOLKA
金额:
$20.0万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-20 至 2012-06-19
关键词:
AbdomenAlgorithmsBiopsyCalibrationCancer DetectionCattleClinicalComputer SystemsComputer softwareDataDetectionDiagnostic Neoplasm StagingGeneric DrugsHumanImageImageryLesionLifeLightLinuxLiverMeasurableMeasuresMethodsModalityMorphologic artifactsMotionNeedle biopsy procedureNeedlesNeoplasm MetastasisPerformancePreparationPrimary NeoplasmProceduresProcessRadio-OpaqueRecoverySeriesSkinSmall Business Innovation Research GrantSoftware ToolsStreamStructureSurfaceSystemTestingTimeUltrasonographyUnited States National Institutes of HealthUpdateWeightWorkbasecancer diagnosiscancer imagingcancer therapycone-beam computed tomographycostgraphical user interfaceimaging modalityimprovedinstrumentlaptopprototypereconstructionresearch studytoolvision development
中文摘要
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英文摘要
Detection and treatment of primary and metastatic tumors, particularly in early stage cancer, continues to be a significant challenge. The technical objective of this SBIR project is to demonstrate that combining real-time surface information with traditional imaging modalities can realize substantial improvements to cancer detection and treatment. Surface information can also provide an additional information channel during CT reconstruction to reduce truncation artifacts and enhance image quality. Surface registration integrated into an ultrasound probe can be used to enhance US/CT fusion for visualization. Needle tracking, supported by surface reconstruction, can provide improved targeting for biopsy or ablative therapies. This SBIR project will develop generic software tools that are able to support these capabilities. These tools include: 1) software for surface reconstruction using real-time structured-light stereo, and 2) surface registration and needle tracking algorithms that are compatible with ultrasound-guided biopsy. These algorithms will provide support for needle-based procedures by providing low-cost, compact precision navigation based on preoperative imagery. Algorithm performance will be demonstrated on a benchtop system for performing biopsy. Measurable endpoints will include the time to perform a biopsy, the overall navigation accuracy, and the target registration error.
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