Publications

Export 343 results:
2021
2020
2019
2018
Bera, K, Velcheti V, Madabhushi A.  2018.  Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications.. American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting. 38:1008-1018. Abstract
2017
Gurcan, MN, Tomaszewski JE, Madabhushi A.  2017.  Special Section Guest Editorial: Digital Pathology.. Journal of medical imaging (Bellingham, Wash.). 4(2):021101.
Janowczyk, A, Basavanhally A, Madabhushi A.  2017.  Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. 57:50-61. Abstract
2016
Janowczyk, A, Basavanhally A, Madabhushi A.  2016.  Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. Abstract
2015
2014
Ali, S, Veltri R, Epstein JI, Christudass C, Madabhushi A.  2014.  Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays.. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society. 14:00176-1. Abstract
Prasanna, P, Tiwari P, Madabhushi A.  2014.  Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 8675:73-80.
Wang, H, Singanamalli A, Ginsburg S, Madabhushi A.  2014.  Selecting Features with Group-Sparse Nonnegative Supervised Canonical Correlation Analysis (GNCCA): Multimodal Prostate Cancer Prognosis. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 8675:385-392.
2013
Lee, G, Ali S, Veltri R, Epstein JI, Christudass C, Madabhushi A.  2013.  Cell Orientation Entropy (COrE): Predicting Biochemical Recurrence from Prostate Cancer Tissue Microarrays. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 8151:396-403.
Prasanna, P, Jain S, Bhagat N, Madabhushi A.  2013.  Decision support system for detection of diabetic retinopathy using smartphones. International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth). :176-179.
Ali, S, Lewis JS, Madabhushi A.  2013.  Spatially Aware Cell Cluster(SpACCl) Graphs: Predicting Outcome in Oropharyngeal p16+ Tumors. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 8149:412-419.
Ginsburg, SB, Ali S, Lee G, Basavanhally A, Madabhushi A.  2013.  Variable Importance in Nonlinear Kernels (VINK): Classification of Digitized Histopathology. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 8150:238-245.
2012
Monaco, JP, Hipp J, Lucas D, Smith SC, Balis U, Madabhushi A.  2012.  Image segmentation with implicit color standardization using spatially constrained expectation maximization: detection of nuclei.. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 15(Pt 1):365-72. Abstract
Toth, R, Madabhushi A.  2012.  Deformable Landmark-Free Active Appearance Models: Application to Segmentation of Multi-institutional Prostate MRI Data. The Medical Image Computing and Computer Assisted Intervention Society (MICCAI) Grand Challenge: Prostate MR Image Segmentation (PROMISE).
2011
Yu, E, Monaco JP, Tomaszewski JE, Shih N, Feldman MD, Madabhushi A.  2011.  Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models. IEEE International Conference of Engineering in Medicine and Biology Society (EMBS). :3427-3430.
Golugula, A, Lee G, Madabhushi A.  2011.  Evaluating feature selection strategies for high dimensional, small sample size datasets. IEEE International Conference of Engineering in Medicine and Biology Society (EMBS). :949-952.
Galaro, J, Judkins AR, Ellison D, Baccon J, Madabhushi A.  2011.  An integrated texton and bag of words classifier for identifying anaplastic medulloblastomas. IEEE International Conference of Engineering in Medicine and Biology Society (EMBS). :3443-3446.
Palumbo, D, Yee B, O'Dea P, Leedy S, Viswanath SE, Madabhushi A.  2011.  Interplay between bias field correction, intensity standardization, and noise filtering for T2-weighted MRI. IEEE International Conference of Engineering in Medicine and Biology Society (EMBS). :5080-5083.
Ali, S, Veltri R, Epstein JI, Christudass C, Madabhushi A.  2011.  Adaptive Energy Selective Active Contour with Shape Priors for Nuclear Segmentation and Gleason Grading of Prostate Cancer. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) . 6891:661–669.
Xiao, G, Madabhushi A.  2011.  Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) . 6893:33–40.
Ginsburg, SB, Tiwari P, Kurhanewicz J, Madabhushi A.  2011.  Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading. Workshop on Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention (in conjunction with MICCAI) . 6963:146-157.
Tiwari, P, Viswanath SE, Kurhanewicz J, Madabhushi A.  2011.  Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate. Workshop on Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention (in conjunction with MICCAI). 6963:80-91.
2010
Xu, J, Sparks R, Janowczyk A, Tomaszewski JE, Feldman MD, Madabhushi A.  2010.  High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies. Workshop on Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention (in conjunction with MICCAI). 6367:77-88.
Xu, J, Monaco JP, Madabhushi A.  2010.  Markov Random Field driven Region-Based Active Contour Model (MaRACel): Application to Medical Image Segmentation. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 6363:197-204.
Sparks, R, Madabhushi A.  2010.  Novel Morphometric based Classification via Diffeomorphic based Shape Representation using Manifold Learning. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 6363:658-665.
2009
Jog, A, Joshi A, Chandran S, Madabhushi A.  2009.  Classifying Ayurvedic Pulse Diagnosis via Concensus Locally Linear Embedding. International Conference on Bio-inspired Systems and Signal Processing (Biosignals). :388-95.
Tomaszewski, JE, Feldman MD, Madabhushi A.  2009.  Fused Diagnostics. Critical Values. 2(3):18-22.
Doyle, S, Madabhushi A, Feldman MD, Tomaszewski JE, Monaco JP.  2009.  A Novel Active Learning Methodology that accounts for Minority Class Problems: Applications to Histopathology. Workshop on Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy (OPTIMHisE) (in conjunction with MICCAI).
Tiwari, P, Rosen M, Reed G, Kurhanewicz J, Madabhushi A.  2009.  Spectral embedding based probabilistic boosting tree (ScEPTre): classifying high dimensional heterogeneous biomedical data. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 5762:844-51. Abstract
Monaco, JP, Viswanath SE, Madabhushi A.  2009.  Weighted Iterated Conditional Modes for Random Fields: Application to Prostate Cancer Detection. Workshop on Probabalistic Models for Medical Image Analysis (PMMIA) (in conjunction with MICCAI). :209-219.
2008
Tiwari, P, Rosen M, Madabhushi A.  2008.  Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 5242:330-338. Abstract
Toth, R, Chappelow J, Rosen M, Pungavkar S, Kalyanpur A, Madabhushi A.  2008.  Multi-attribute Non-Initializing Texture Reconstruction based Active Shape Model (MANTRA). International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 5241:653-61. Abstract
2007
Tiwari, P, Madabhushi A, Rosen M.  2007.  A hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS). International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 4792:278-86. Abstract
Doyle, S, Hwang, M, Naik S, Feldman MD, Tomaszewski JE, Madabhushi A.  2007.  Using manifold learning for content-based image retrieval of prostate histopathology. Workshop on Content-Based Image Retrieval for Biomedical Image Archives (in conjunction with MICCAI). :53-62.
2006
Doyle, S, Madabhushi A, Feldman MD, Tomaszewski JE.  2006.  A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). 4191:504-11. Abstract
Wu, Y, Wang, C., Ng, S.C., Madabhushi A, Zhong YX.  2006.  Breast Cancer Diagnosis Using Neural-based Linear Fusion Strategies. International Conference on Neural Information Processing (ICONIP). 4234:165-175.
Madabhushi, A, Rosen M, Tomaszewski JE, Feldman MD.  2006.  Eliminating mislabeled training instances: Detecting Prostate Cancer from High Resolution MRI. Workshop on Medical Image Processing in Oncology (In conjunction with MICCAI). :24-31.
2005
2004
2003
2002
2000
Madabhushi, A, Aggarwal JK.  2000.  Using the Movement of the Head to Recognize Human Activity. International Conference on Pattern Recognition (ICPR). 4:698-701.
1999
Madabhushi, A, Aggarwal JK.  1999.  A Bayesian Approach to Human Activity Recognition. IEEE Workshop on Visual Surveillance Systems. :25-32.

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