Madabhushi A - Search Results

1

Multi-attribute non-initializing texture reconstruction based active shape model (MANTRA).

Toth R, Chappelow J, Rosen M, Pungavkar S, Kalyanpur A, Madabhushi A. Toth R, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2008;11(Pt 1):653-61. doi: 10.1007/978-3-540-85988-8_78. Med Image Comput Comput Assist Interv. 2008. PMID: 18979802

2

Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI.

Madabhushi A, Feldman MD, Metaxas DN, Tomaszeweski J, Chute D. Madabhushi A, et al. IEEE Trans Med Imaging. 2005 Dec;24(12):1611-25. doi: 10.1109/TMI.2005.859208. IEEE Trans Med Imaging. 2005. PMID: 16350920 Clinical Trial.

3

Graph embedding to improve supervised classification and novel class detection: application to prostate cancer.

Madabhushi A, Shi J, Rosen M, Tomaszeweski JE, Feldman MD. Madabhushi A, et al. Med Image Comput Comput Assist Interv. 2005;8(Pt 1):729-37. doi: 10.1007/11566465_90. Med Image Comput Comput Assist Interv. 2005. PMID: 16685911

4

New methods of MR image intensity standardization via generalized scale.

Madabhushi A, Udupa JK. Madabhushi A, et al. Med Phys. 2006 Sep;33(9):3426-34. doi: 10.1118/1.2335487. Med Phys. 2006. PMID: 17022239

Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal intensity variations (non-standardness) inherent in Magnetic Resonance (MR) images. ...The new scale-based methods were found to be better t …

Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal …

5

A boosting cascade for automated detection of prostate cancer from digitized histology.

Doyle S, Madabhushi A, Feldman M, Tomaszeweski J. Doyle S, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2006;9(Pt 2):504-11. doi: 10.1007/11866763_62. Med Image Comput Comput Assist Interv. 2006. PMID: 17354810

6

Distinguishing lesions from posterior acoustic shadowing in breast ultrasound via non-linear dimensionality reduction.

Madabhushi A, Yang P, Rosen M, Weinstein S. Madabhushi A, et al. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:3070-3. doi: 10.1109/IEMBS.2006.260189. Conf Proc IEEE Eng Med Biol Soc. 2006. PMID: 17947006

7

Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach.

Doyle S, Rodriguez C, Madabhushi A, Tomaszeweski J, Feldman M. Doyle S, et al. Among authors: madabhushi a. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:4759-62. doi: 10.1109/IEMBS.2006.260188. Conf Proc IEEE Eng Med Biol Soc. 2006. PMID: 17947116

8

A hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS).

Tiwari P, Madabhushi A, Rosen M. Tiwari P, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2007;10(Pt 2):278-86. doi: 10.1007/978-3-540-75759-7_34. Med Image Comput Comput Assist Interv. 2007. PMID: 18044579 Free PMC article.

9

A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI.

Viswanath S, Bloch BN, Genega E, Rofsky N, Lenkinski R, Chappelow J, Toth R, Madabhushi A. Viswanath S, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2008;11(Pt 1):662-9. doi: 10.1007/978-3-540-85988-8_79. Med Image Comput Comput Assist Interv. 2008. PMID: 18979803 Free PMC article.

10

Consensus-locally linear embedding (C-LLE): application to prostate cancer detection on magnetic resonance spectroscopy.

Tiwari P, Rosen M, Madabhushi A. Tiwari P, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2008;11(Pt 2):330-8. doi: 10.1007/978-3-540-85990-1_40. Med Image Comput Comput Assist Interv. 2008. PMID: 18982622

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