Connecting Radiology | Enabling collaboration and professional development
Informatics in radiology: GridCAD: grid-based computer-aided detection system.
Pan TC, Gurcan MN, Langella SA, Oster SW, Hastings SL, Sharma A, Rutt BG, Ervin DW, Kurc TM, Siddiqui KM, Saltz JH, Siegel EL.
Department of Biomedical Informatics, Ohio State University, 3190 Graves Hall, 333 W 10th Ave, Columbus, OH 43210, USA. tpan@bmi.osu.edu
Radiographics. 2007 May-Jun;27(3):889-97.
Grid computing-the use of a distributed network of electronic resources to cooperatively perform subsets of computationally intensive tasks-may help improve the speed and accuracy of radiologic image interpretation by enabling collaborative computer-based and human readings. GridCAD, a software application developed by using the National Cancer Institute Cancer Biomedical Informatics Grid architecture, implements the fundamental elements of grid computing and demonstrates the potential benefits of grid technology for medical imaging. It allows users to query local and remote image databases, view images, and simultaneously run multiple computer-assisted detection (CAD) algorithms on the images selected. The prototype CAD systems that are incorporated in the software application are designed for the detection of lung nodules on thoracic computed tomographic images. GridCAD displays the original full-resolution images with an overlay of nodule candidates detected by the CAD algorithms, by human observers, or by a combination of both types of readers. With an underlying framework that is computer platform independent and scalable to the task, the software application can support local and long-distance collaboration in both research and clinical practice through the efficient, secure, and reliable sharing of resources for image data mining, analysis, and archiving. (c) RSNA, 2007.
Posted via PubMed for educational and discussion purposes only.
Link to PubMed Reference
Department of Biomedical Informatics, Ohio State University, 3190 Graves Hall, 333 W 10th Ave, Columbus, OH 43210, USA. tpan@bmi.osu.edu
Radiographics. 2007 May-Jun;27(3):889-97.
Grid computing-the use of a distributed network of electronic resources to cooperatively perform subsets of computationally intensive tasks-may help improve the speed and accuracy of radiologic image interpretation by enabling collaborative computer-based and human readings. GridCAD, a software application developed by using the National Cancer Institute Cancer Biomedical Informatics Grid architecture, implements the fundamental elements of grid computing and demonstrates the potential benefits of grid technology for medical imaging. It allows users to query local and remote image databases, view images, and simultaneously run multiple computer-assisted detection (CAD) algorithms on the images selected. The prototype CAD systems that are incorporated in the software application are designed for the detection of lung nodules on thoracic computed tomographic images. GridCAD displays the original full-resolution images with an overlay of nodule candidates detected by the CAD algorithms, by human observers, or by a combination of both types of readers. With an underlying framework that is computer platform independent and scalable to the task, the software application can support local and long-distance collaboration in both research and clinical practice through the efficient, secure, and reliable sharing of resources for image data mining, analysis, and archiving. (c) RSNA, 2007.
Posted via PubMed for educational and discussion purposes only.
Link to PubMed Reference
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