Stroke Suite: Cad Systems for Acute Ischemic Stroke, Hemorrhagic Stroke, and Stroke in ER

We present a suite of computer aided-diagnosis (CAD) systems for acute ischemic stroke, hemorrhagic stroke, and stroke in emergency room. A software architecture common for them is described. The acute ischemic stroke CAD system supports thrombolysis. Our approach shifts the paradigm from a 2D visual inspection of individual scans/maps to atlas-assisted quantification and simultaneous visualization of multiple 2D/3D images. The hemorrhagic stroke CAD system supports the evacuation of hemorrhage by thrombolytic treatment. It aims at progression and quantification of blood clot removal. The clot is automatically segmented from CT time series, its volume measured, and displayed in 3D along with a catheter. A stroke CAD in emergency room enables rapid atlas-assisted decision support regarding the stroke and its location. Our stroke CAD systems facilitate and speed up image analysis, increase confidence of interpreters, and support decision making. They are potentially useful in diagnosis and research, particularly, for clinical trials.

[1]  Guoyu Qian,et al.  Analysis of ischemic stroke MR images by means of brain atlases of anatomy and blood supply territories. , 2006, Academic radiology.

[2]  J. Grotta,et al.  Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials , 2004, The Lancet.

[3]  R. Jeffrey,et al.  Computed Tomography Colonography: Feasibility of Computer-Aided Polyp Detection in a “First Reader” Paradigm , 2004, Journal of computer assisted tomography.

[4]  Stephen M. Davis,et al.  Therapeutic Impact of MRI in Acute Stroke , 2006 .

[5]  Ihar Volkau,et al.  Rapid and automatic calculation of the midsagittal plane in magnetic resonance diffusion and perfusion images. , 2006, Academic radiology.

[6]  Varsha Gupta,et al.  Automatic and rapid identification of infarct slices and hemisphere in DWI scans. , 2008, Academic radiology.

[7]  Yulei Jiang.  Computer-Aided Diagnosis of Breast Cancer in Mammography: Evidence and Potential , 2002, Technology in cancer research & treatment.

[8]  Yu Qiao,et al.  Thresholding based on variance and intensity contrast , 2007, Pattern Recognit..

[9]  Wieslaw Lucjan Nowinski,et al.  The cerefy brain atlases , 2007, Neuroinformatics.

[10]  Wieslaw L. Nowinski,et al.  Electronic Brain Atlases: Features and Applications , 2002 .

[11]  W. L. Nowinski,et al.  Modified Talairach Landmarks , 2001, Acta Neurochirurgica.

[12]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[13]  D. Caramella,et al.  3D Image Processing: Techniques and Clinical Applications , 2002 .

[14]  W L Nowinski,et al.  Multiple brain atlas database and atlas-based neuroimaging system. , 1997, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[15]  M. Torrens.  Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[16]  Qingmao Hu,et al.  Informatics in Radiology (infoRAD): three-dimensional atlas of the brain anatomy and vasculature. , 2005, Radiographics : a review publication of the Radiological Society of North America, Inc.

[17]  Max A. Viergever,et al.  Computer-aided diagnosis in chest radiography: a survey , 2001, IEEE Transactions on Medical Imaging.

[18]  A. Aziz,et al.  Fast Talairach Transformation for Magnetic Resonance Neuroimages , 2006, Journal of computer assisted tomography.

[19]  T. Back,et al.  Magnetic resonance imaging in ischemic stroke , 2006 .

[20]  Osmo Tervonen,et al.  Computer-assisted diagnosis by temporal subtraction in postoperative brain tumor patients: a feasibility study. , 2004, Academic radiology.