Madabhushi A - Search Results

1

A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Romo-Bucheli D, Janowczyk A, Gilmore H, Romero E, Madabhushi A. Romo-Bucheli D, et al. Among authors: madabhushi a. Cytometry A. 2017 Jun;91(6):566-573. doi: 10.1002/cyto.a.23065. Epub 2017 Feb 13. Cytometry A. 2017. PMID: 28192639 Free PMC article.

2

Hierarchical normalized cuts: unsupervised segmentation of vascular biomarkers from ovarian cancer tissue microarrays.

Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, Madabhushi A. Janowczyk A, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2009;12(Pt 1):230-8. doi: 10.1007/978-3-642-04268-3_29. Med Image Comput Comput Assist Interv. 2009. PMID: 20425992

3

A high-throughput active contour scheme for segmentation of histopathological imagery.

Xu J, Janowczyk A, Chandran S, Madabhushi A. Xu J, et al. Among authors: madabhushi a. Med Image Anal. 2011 Dec;15(6):851-62. doi: 10.1016/j.media.2011.04.002. Epub 2011 Apr 28. Med Image Anal. 2011. PMID: 21570336 Free PMC article.

4

High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts.

Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, Madabhushi A. Janowczyk A, et al. Among authors: madabhushi a. IEEE Trans Biomed Eng. 2012 May;59(5):1240-52. doi: 10.1109/TBME.2011.2179546. Epub 2011 Dec 13. IEEE Trans Biomed Eng. 2012. PMID: 22180503

5

A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides.

Cruz-Roa A, González F, Galaro J, Judkins AR, Ellison D, Baccon J, Madabhushi A, Romero E. Cruz-Roa A, et al. Among authors: madabhushi a. Med Image Comput Comput Assist Interv. 2012;15(Pt 1):157-64. doi: 10.1007/978-3-642-33415-3_20. Med Image Comput Comput Assist Interv. 2012. PMID: 23285547

6

Quantifying local heterogeneity via morphologic scale: Distinguishing tumoral from stromal regions.

Janowczyk A, Chandran S, Madabhushi A. Janowczyk A, et al. Among authors: madabhushi a. J Pathol Inform. 2013 Mar 30;4(Suppl):S8. doi: 10.4103/2153-3539.109865. Print 2013. J Pathol Inform. 2013. PMID: 23766944 Free PMC article.

7

Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis.

Xu J, Xiang L, Wang G, Ganesan S, Feldman M, Shih NN, Gilmore H, Madabhushi A. Xu J, et al. Among authors: madabhushi a. Comput Med Imaging Graph. 2015 Dec;46 Pt 1:20-29. doi: 10.1016/j.compmedimag.2015.04.002. Epub 2015 Apr 28. Comput Med Imaging Graph. 2015. PMID: 25958195

8

Predicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer.

Basavanhally A, Viswanath S, Madabhushi A. Basavanhally A, et al. Among authors: madabhushi a. PLoS One. 2015 May 18;10(5):e0117900. doi: 10.1371/journal.pone.0117900. eCollection 2015. PLoS One. 2015. PMID: 25993029 Free PMC article.

9

Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.

Wang H, Cruz-Roa A, Basavanhally A, Gilmore H, Shih N, Feldman M, Tomaszewski J, Gonzalez F, Madabhushi A. Wang H, et al. Among authors: madabhushi a. J Med Imaging (Bellingham). 2014 Oct;1(3):034003. doi: 10.1117/1.JMI.1.3.034003. Epub 2014 Oct 10. J Med Imaging (Bellingham). 2014. PMID: 26158062 Free PMC article.

10

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images.

Xu J, Xiang L, Liu Q, Gilmore H, Wu J, Tang J, Madabhushi A. Xu J, et al. Among authors: madabhushi a. IEEE Trans Med Imaging. 2016 Jan;35(1):119-30. doi: 10.1109/TMI.2015.2458702. Epub 2015 Jul 20. IEEE Trans Med Imaging. 2016. PMID: 26208307 Free PMC article.

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