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Anant Madabhushi: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Anant Madabhushi, Jianbo Shi, Michael D. Feldman, Mark Rosen, John Tomaszewski
    Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI. [Citation Graph (0, 0)][DBLP]
    CVAMIA, 2006, pp:25-36 [Conf]
  2. Yunfeng Wu, Cong Wang, Sin Chun Ng, Anant Madabhushi, Yixin Zhong
    Breast Cancer Diagnosis Using Neural-Based Linear Fusion Strategies. [Citation Graph (0, 0)][DBLP]
    ICONIP (3), 2006, pp:165-175 [Conf]
  3. Anant Madabhushi, J. K. Aggarwal
    Using Head Movement to Recognize Activity. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:4698-4701 [Conf]
  4. Anant Madabhushi, Dimitris N. Metaxas
    Automatic boundary extraction of ultrasonic breast lesions. [Citation Graph (0, 0)][DBLP]
    ISBI, 2002, pp:601-604 [Conf]
  5. Scott Doyle, Anant Madabhushi, Michael D. Feldman, John E. Tomaszeweski
    A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology. [Citation Graph (0, 0)][DBLP]
    MICCAI (2), 2006, pp:504-511 [Conf]
  6. Anant Madabhushi, Michael D. Feldman, Dimitris N. Metaxas, Deborah Chute, John E. Tomaszeweski
    A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI. [Citation Graph (0, 0)][DBLP]
    MICCAI (1), 2003, pp:581-591 [Conf]
  7. Anant Madabhushi, Jianbo Shi, Mark Rosen, John E. Tomaszeweski, Michael D. Feldman
    Graph Embedding to Improve Supervised Classification and Novel Class Detection: Application to Prostate Cancer. [Citation Graph (0, 0)][DBLP]
    MICCAI, 2005, pp:729-737 [Conf]
  8. Anant Madabhushi, Jayaram K. Udupa, Andre Souza
    Generalized scale: Theory, algorithms, and application to image inhomogeneity correction. [Citation Graph (0, 0)][DBLP]
    Computer Vision and Image Understanding, 2006, v:101, n:2, pp:100-121 [Journal]
  9. Anant Madabhushi, Michael D. Feldman, Dimitris N. Metaxas, John E. Tomaszeweski, Deborah Chute
    Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Med. Imaging, 2005, v:24, n:12, pp:1611-1625 [Journal]
  10. Anant Madabhushi, Dimitris N. Metaxas
    Combining Low, High-Level and Empirical Domain Specific Knowledge for Automated Segmentation of Ultrasonic Breast Lesions. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Med. Imaging, 2003, v:22, n:2, pp:155-169 [Journal]
  11. Anant Madabhushi, Jayaram K. Udupa
    Interplay between intensity standardization and inhomogeneity correction in MR image processing. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Med. Imaging, 2005, v:24, n:5, pp:561-576 [Journal]
  12. Pallavi Tiwari, Anant Madabhushi, Mark Rosen
    A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS). [Citation Graph (0, 0)][DBLP]
    MICCAI (2), 2007, pp:278-286 [Conf]
  13. George Lee, Carlos Rodriguez, Anant Madabhushi
    An Empirical Comparison of Dimensionality Reduction Methods for Classifying Gene and Protein Expression Datasets. [Citation Graph (0, 0)][DBLP]
    ISBRA, 2007, pp:170-181 [Conf]

  14. Expectation Maximization driven Geodesic Active Contour with Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology. [Citation Graph (, )][DBLP]


  15. Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology. [Citation Graph (, )][DBLP]


  16. Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features. [Citation Graph (, )][DBLP]


  17. Automated Grading of Prostate Cancer Using Architectural and Textural Image Features. [Citation Graph (, )][DBLP]


  18. A Combined Feature Ensemble Based Mutual Information Scheme for Robust Inter-Modal, Inter-Protocol Image Registration. [Citation Graph (, )][DBLP]


  19. Computer-Aided Prognosis of ER+ Breast Cancer Histopathology and Correlating Survival Outcome with Oncotype DX Assay. [Citation Graph (, )][DBLP]


  20. Segmentation and Classification of Triple Negative Breast Cancers Using DCE-MRI. [Citation Graph (, )][DBLP]


  21. A Knowledge Representation Framework for Integration, Classification of Multi-Scale Imaging and Non-Imaging Data: Preliminary Results in Predicting Prostate Cancer Recurrence by Fusing Mass Spectrometry and Histology. [Citation Graph (, )][DBLP]


  22. A Comprehensive Segmentation, Registration, and Cancer Detection Scheme on 3 Tesla In VivoProstate DCE-MRI. [Citation Graph (, )][DBLP]


  23. Multi-Attribute Non-initializing Texture Reconstruction Based Active Shape Model (MANTRA). [Citation Graph (, )][DBLP]


  24. Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays. [Citation Graph (, )][DBLP]


  25. Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. [Citation Graph (, )][DBLP]


  26. Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data. [Citation Graph (, )][DBLP]


  27. High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies. [Citation Graph (, )][DBLP]


  28. Novel Morphometric Based Classification via Diffeomorphic Based Shape Representation Using Manifold Learning. [Citation Graph (, )][DBLP]


  29. Markov Random Field driven Region-Based Active Contour Model (MaRACel): Application to Medical Image Segmentation. [Citation Graph (, )][DBLP]


  30. Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy. [Citation Graph (, )][DBLP]


  31. Semi-Supervised Graph Embedding Scheme with Active Learning (SSGEAL): Classifying High Dimensional Biomedical Data. [Citation Graph (, )][DBLP]


  32. Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis. [Citation Graph (, )][DBLP]


  33. Classifying Ayurvedic Pulse Signals Via Consensus Locally Linear Embedding. [Citation Graph (, )][DBLP]


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