Integrating structural and functional imaging for computer assisted detection of prostate cancer on multi-protocol in vivo 3 Tesla MRI
暂无分享,去创建一个
Anant Madabhushi | Robert Toth | Mark Rosen | Arjun Kalyanpur | B. Nicolas Bloch | Elizabeth Genega | Neil Rofsky | Robert E. Lenkinski | Satish Viswanath | Jonathan Chappelow | R. Lenkinski | B. Bloch | N. Rofsky | A. Madabhushi | J. Chappelow | M. Rosen | S. Viswanath | E. Genega | R. Toth | A. Kalyanpur
[1] David G. Stork,et al. Pattern Classification , 1973 .
[2] Pieter C. Vos,et al. Combining T2-weighted with dynamic MR images for computerized classification of prostate lesions , 2008, SPIE Medical Imaging.
[3] Bernd Hamm,et al. Patients with a history of elevated prostate-specific antigen levels and negative transrectal US-guided quadrant or sextant biopsy results: value of MR imaging. , 2002, Radiology.
[4] A. Wunderlich,et al. Multimodal Cranial Neuronavigation: Direct Integration of Functional Magnetic Resonance Imaging and Positron Emission Tomography Data: Technical Note , 2001, Neurosurgery.
[5] Anant Madabhushi,et al. Multimodal image registration of ex vivo 4 Tesla MRI with whole mount histology for prostate cancer detection , 2007, SPIE Medical Imaging.
[6] Anant Madabhushi,et al. A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging , 2008, SPIE Medical Imaging.
[7] C. Kim,et al. Localization of Prostate Cancer Using 3T MRI: Comparison of T2-Weighted and Dynamic Contrast-Enhanced Imaging , 2006, Journal of computer assisted tomography.
[8] Kevin J Parker,et al. Three-dimensional registration of prostate images from histology and ultrasound. , 2004, Ultrasound in medicine & biology.
[9] Torsten Rohlfing,et al. Information Fusion in Biomedical Image Analysis: Combination of Data vs. Combination of Interpretations , 2005, IPMI.
[10] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[11] Dimitris N. Metaxas,et al. Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI , 2005, IEEE Transactions on Medical Imaging.
[12] Olivier Rouvière,et al. Evaluation of T2-weighted and dynamic contrast-enhanced MRI in localizing prostate cancer before repeat biopsy , 2009, European Radiology.
[13] Robert E Lenkinski,et al. Prostate cancer: accurate determination of extracapsular extension with high-spatial-resolution dynamic contrast-enhanced and T2-weighted MR imaging--initial results. , 2007, Radiology.
[14] Anant Madabhushi,et al. COLLINARUS: collection of image-derived non-linear attributes for registration using splines , 2009, Medical Imaging.
[15] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[16] Jayaram K. Udupa,et al. New methods of MR image intensity standardization via generalized scale , 2005, SPIE Medical Imaging.
[17] Anant Madabhushi,et al. A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In VivoProstate DCE-MRI , 2008, MICCAI.
[18] Anant Madabhushi,et al. Multi-Attribute Non-initializing Texture Reconstruction Based Active Shape Model (MANTRA) , 2008, MICCAI.
[19] Thomas Hambrock,et al. Computerized analysis of prostate lesions in the peripheral zone using dynamic contrast enhanced MRI. , 2008, Medical physics.
[20] William Wells,et al. Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted magnetic resonance imaging; a multichannel statistical classifier. , 2003, Medical physics.
[21] Anant Madabhushi,et al. A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery , 2008, SPIE Medical Imaging.
[22] D P Dearnaley,et al. Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. , 2000, Clinical radiology.