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2009 (top)

71. Tomaszewski, J., Feldman, M., Madabhushi, A., "Fused Diagnostics", Critical Values, Vol. 2(3), pp. 20-22, 2009 (Invited). (PDF)
70. Madabhushi, A., "Digital Pathology Image Analysis: Opportunities and Challenges", Imaging in Medicine, Vol. 1(1), pp. 7-10, 2009 (Editorial). (PDF)
69. Tiwari, P., Rosen, M., Madabhushi, A., "A Hierarchical Spectral Clustering and Non-linear Dimensionality Reduction Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy", Medical Physics, Vol. 36(9), pp. 3927-39, 2009. (PDF)
    
68. Alexe, G., Monaco, J., Doyle, S., Basavanhally, A., Reddy, A., Seiler, M., Ganesan, S., Bhanot, G., Madabhushi, A., "Towards Improved Cancer Diagnosis and Prognosis Using Analysis of Gene Expression Data and Computer Aided Imaging", Experimental Biology and Medicine, Vol. 234, pp. 860-879, 2009. (PDF)
    
67. Tiwari, P., Viswanath,S., Rosen, M., Reed, G., Kurhanewicz, J., Madabhushi, A., "Multi-modal integration of magnetic resonance imaging and spectroscopy for detection of prostate cancer", Biosignal Interpretation, 2009.
66. Doyle, S., Madabhushi, A., Feldman, M., Tomaszewski, J., Monaco, J., “A Novel Active Learning Methodology that accounts for Minority Class Problems: Applications to Histopathology”, in Optical Tissue Image analysis in Microscopy, Histopathology and Endoscopy (OPTIMHisE) (in conjunction with MICCAI), 2009. (PDF)
    
65. Monaco, J., Viswanath, S., Madabhushi, A., "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), 2009. (PDF)
    
64. Janowczyk, A., Chandran, S., Singh, R., Sasaroli, D., Coukos, G., Feldman, M, Madabhushi, A., "Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays", in MICCAI, LNCS 5761, p. 230-238, 2009. (PDF)
    
63. Tiwari, P., Rosen, M., Reed, G., Kurhanewicz, J., Madabhushi, A., "Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data", in MICCAI, LNCS 5762, pp. 844–851, 2009. (PDF)
    
62. Agner, S C., Xu, J, Fatakdawala, H, Ganesan, S, Madabhushi, A, Englander, S, Rosen, M, Thomas, K, Schnall, M, Feldman, M, Tomaszewski, J, "Segmentation and classification of triple negative breast cancers using DCE-MRI," Biomedical Imaging: From Nano to Macro, pp.1227-1230, 2009. (PDF)
61. Lee, G, Doyle, S, Monaco, J, Madabhushi, A, Feldman, M D., Master, S R., Tomaszewski, J E., "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," Biomedical Imaging: From Nano to Macro, pp.77-80, 2009. (PDF)
60. Basavanhally, A,  Xu, J, Madabhushi, A, Ganesan, S, "Computer-aided prognosis of ER+ breast cancer histopathology and correlating survival outcome with Oncotype DX assay," Biomedical Imaging: From Nano to Macro, pp.851-854, 2009. (PDF)
59. Fatakdawala, H, Basavanhally, A, Xu, J, Bhanot, G, Ganesan, S, Feldman, M, Tomaszewski, J, Madabhushi, A, "Expectation Maximization Driven Geodesic Active Contour: Application to Lymphocyte Segmentation on Digitized Breast Cancer Histopathology", Bioinformatics and BioEngineering, 2009. BIBE '09. Ninth IEEE International Conference on, pp.69-76, 22-24 June 2009. (PDF)
    
58. Naik, J, Doyle, S, Basavanhally, A, Ganesan, S, Feldman, M, Tomaszewski, J, Madabhushi, A, "A Boosted Distance Metric: Application to Content Based Image Retrieval and Classification of Digitized Histopathology", SPIE Medical Imaging, vol. 7260, 2009. (Honorable Mention) (PDF)
    
57. Monaco, J, Tomaszewski, J, Feldman, M, Mehdi, M, Mousavi, P, Boag, A, Davidson, C, Abolmaesumi, P, and Madabhushi, A, "Probabilistic Pair-wise Markov Models: Application to Prostate Cancer Detection", SPIE Medical Imaging, vol. 7260, 2009. (PDF)
    
56. Viswanath, S, Bloch, B. N., Rosen, M, Chappelow, J, Rofsky, N., Lenkinski, R., Genega, E., Kalyanpur, A, Madabhushi, A,  "Integrating Structural and Functional Imaging for Computer Assisted Detection of Prostate Cancer on Multi-Protocol in vivo 3 Tesla MRI", SPIE Medical Imaging, vol. 7260, 2009. (PDF)
    
55. Toth, R, Doyle, S, Pungavkar, S, Kalyanpur, A, Madabhushi, A, "A Boosted Ensemble Scheme for Accurate Landmark Detection for Active Shape Models", SPIE Medical Imaging, vol. 7260, 2009. (Awarded Michael B. Merickel Best Student Paper award) (PDF)
    
54. Chappelow, J., Bloch, N., Rofsky, N, Genega, E, Lenkinski, R, DeWolf, W, Viswanath, S, Madabhushi, A., "COLLINARUS: Collection of Image-derived Non-linear Attributes for Registration Using Splines", SPIE Medical Imaging, vol. 7259, 2009. (PDF)
    
53. Jog, A, Chandran, S, Joshi, A, Madabhushi, A, "Classifying Ayurvedic Pulse Signals Via Consensus Locally Linear Embedding", Biosignals, 2009. (PDF)
    
    

2008 (top)

52. Souza, A, Udupa, J, Madabhushi, A, "Use of Generalized Scale for image filtering", Medical Image Analysis, Vol. 12(2), pp. 87-98, 2008. (PDF)
    
51. Madabhushi, A, Udupa, J, "Generalized Scale" (VDM Verlag Dr. Mueller e.K.), ISBN-10: 383647378X, 2008. (Link)
    
50. Juan, D, Alexe, G, Antes, T, Foran, D, Madabhushi, A, Bhanot, A, Delisi, C, Ganesan, S, Liou, L, "MicroRNA Expression Profile in Clear-Cell Kidney Cancer", The Journal of Urology, Vol. 179 (4), Supplement 1, pp. 92,  2008. (PDF)
49. Lee, G, Rodriguez, C, Madabhushi, A, "Investigating the Efficacy of Nonlinear Dimensionality Reduction Schemes in Classifying Gene- and Protein-Expression Studies", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 5(3), pp. 368 - 384, 2008. (PDF)
48. Doyle, S, Agner, S, Madabhushi, A, Feldman, M, Tomaszewski, J, "Automated Grading of Breast Cancer Histopathology Using Spectral Clustering with Textural and Architectural Image Features", in Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on, pp. 496-499, 2008. (PDF)
47. Naik, S, Doyle, S, Madabhushi, A, Tomaszewski, J, Feldman, M, "Automated Nuclear and Gland Segmentation and Gleason Grading of Prostate Histology by Integrating Low-, High-level and Domain Specific Information", Special Workshop on Computational Histopathology (CHIP), in conjunction with 5th IEEE International Symposium on Biomedical Imaging (Invited Paper), pp. 284 - 287, 2008. (PDF)
46. Madabhushi, A, Chappelow, J, Viswanath, S, Toth, R, Tiwari, P, ‘Multi-protocol Prostate MR Image Analysis: Image Segmentation, Registration, and Computer-aided Diagnosis’, Workshop on Prostate Image Analysis (in Conjunction with MICCAI), 2008.(PDF)
45. Tiwari, P, Rosen, M, Madabhushi, A., "Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy", in MICCAI, Volume 2, pp. 330-338, 2008. (PDF)
44. Viswanath, S, Bloch, BN, Genega, E, Rofsky, N, Lenkinski, R, Chappelow, J, Toth, R. Madabhushi, A, "A Comprehensive Segmentation Registration and Cancer Detection Scheme on 3 Tesla in vivo Prostate DCE MRI", in MICCAI, Vol. 1, pp. 662-669, 2008. (PDF)
43. Toth, R, Chappelow, J, Rosen, M, Kalyanpur, A, Pungavkar, S, Madabhushi, A. "Multi-attribute Non-Initializing Texture Reconstruction based ASM (MANTRA)", in MICCAI, Vol. 1, pp. 653-661, 2008. (PDF)
42. Monaco, J, Tomaszewski, J, Feldman, M,  Moradi, M, Mousavi, P, Boag, A, Davidson, C, Abolmaesumi, P, Madabhushi, A, "Detection of Prostate Cancer from Whole-Mount Histology Images Using Markov Random Fields", Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI), 2008. (PDF)
41. Basavanhally, A, Agner, S, Alexe, G, Bhanot, G, Ganesan, S, Madabhushi, A, "Manifold learning with graph-based features for identifying extent of lymphocytic infiltration from high grade breast cancer histology", Workshop on Microscopic Image Analysis with Applications in Biology (in conjunction with MICCAI), 2008. (PDF)
40. Chappelow, J.C., Viswanath, S, Madabhushi, A., Rosen, M., Tomaszewski, J., Feldman, M., "Improving Supervised Classification Accuracy using Non-rigid Multimodal Image Registration: Computer-Aided Detection of Prostate Cancer on ex vivo MRI", SPIE Medical Imaging, Vol. 6915, 2008. (PDF)
39. Viswanath, S, Rosen, M, Madabhushi, A,  "A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery", SPIE Medical Imaging, Vol. 6915, 2008. (PDF)
38. Toth, R, Tiwari, P, Rosen, M, Madabhushi, A, Kalyanpur, A, Pungavkar, S, An Integrated Multi-modal Prostate Segmentation Scheme by Combining Magnetic Resonance Spectroscopy and Active Shape Models, SPIE Medical Imaging, Vol. 6914, 2008. (PDF)
37. Agner, S, Soman, S, Libfeld, E, McDonald, M, Rosen, M, Schnall, MD, Chin, D, Nosher, J, Madabhushi, A, "Novel kinetic texture features for breast lesion classification on dynamic contrast enhanced (DCE) MRI", SPIE Medical Imaging, vol. 6915, 2008. (PDF)
36. Viswanath, S, Tiwari, P, Rosen, M, Madabhushi, A, "A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging", SPIE Medical Imaging, vol. 6915, 2008. (PDF)

2007 (top)

35. Chappelow, J, Madabhushi, A, Rosen, M, Tomasezweski, J, Feldman, M, "A Combined Feature Ensemble based Mutual Information Scheme for robust Inter-Modal, Inter-Protocol Image Registration", International Symposium on Biomedical Imaging (ISBI), pp. 644-47, 2007. (PDF)
34. Doyle, S, Hwang, M, Shah, K, Madabhushi, A, Tomasezweski, J, Feldman, M, "Automated Grading of Prostate Cancer using Architectural and Textural Image Features", International Symposium on Biomedical Imaging (ISBI), pp. 1284-87, 2007. (PDF)
33. Lee, G, Rodriguez, C, Madabhushi, A, "An Empirical Comparison of Dimensionality Reduction Methods for Classifying Gene and Protein Expression Datasets", ISBRA 2007, LNBI 4463 pp. 170-181, 2007. (PDF)
32. Naik, S, Madabhushi, A, Tomaszeweski, J; Feldman, M, "A Quantitative Exploration of Efficacy of Gland Morphology in Prostate Cancer Grading," IEEE 33rd North East Bioengineering Conference, pp. 58-59, 2007. (PDF)
31. Tiwari, P, Madabhushi, A, Rosen, M, "A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS)", MICCAI, LNCS. 4792, pp. 278-86, 2007. (PDF)
30. Doyle, S, Hwang, M, Naik, S, Feldman, M, Tomaszewwski, J, Madabhushi, A, "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), pp. 53-62, 2007.
29. Naik, S, Doyle, S, Madabhushi, A, Tomaszewski, J, Feldman, M, "Gland Segmentation and Gleason Grading of Prostate Histology by Integrating Low-, High-level and Domain Specific Information", Workshop on Microscopic Image Analysis with Applications in Biology, 2007. (PDF)
28. Chappelow, J, Madabhushi, A, Rosen, M, Tomasezweski, J, Feldman, M, "Multimodal Image Registration of ex vivo 4 Tesla Prostate MRI with Whole Mount Histology for Cancer Detection", SPIE Medical Imaging, vol. 6512(1), pp. S1-S12, 2007. (PDF)

2006 (top)

27. Madabhushi, A, Udupa, J, Souza, A, "Generalized Scale: Theory, Algorithms and Application to Inhomogeneity Correction,""Computer Vision and Image Understanding, Vol. 101, pp. 100-121, 2006. (PDF)
28. Madabhushi, A, Udupa, J, Moonis, G, "Comparing MR Image Intensity Standardization Against Tissue Characterizability of Magnetization Transfer Ratio Imaging", Journal of Magnetic Resonance Imaging, Vol. 24, pp. 667-675, 2006. (PDF)
25. Madabhushi, A, Udupa, J, "New Methods of MR Image Intensity Standardization Via Generalized Scale", Medical Physics, vol. 33(9), pp. 3426-34, 2006. (PDF)
24. Madabhushi, A, Shi, J, Rosen, M, Tomasezweski, J, Feldman, M, "Comparing Classification Performance of Feature Ensembles: Detecting Prostate Cancer from High Resolution MRI", Computer Vision Methods in Medical Image Analysis (in conjunction with ECCV), LNCS 4241, pp. 25-36, 2006. (PDF)
23. Madabhushi, A, Rosen, M, Tomasezweski, J, Feldman, M, "Eliminating mislabeled training instances: Detecting Prostate Cancer from High Resolution MRI", Workshop on Medical Image Processing in Oncology (in conjunction with MICCAI), pp. 24-31, 2006.
22. Doyle, S, Madabhushi, A, Feldman, M, Tomaszeweski, J, "A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology", MICCAI, LNCS. 4191, pp. 504-511, 2006. (PDF)
21. Doyle, S, Rodriguez, C, Madabhushi, A, Tomasezweski, J, Feldman, M, "Detecting Prostatic Adenocarcinoma from Digitized Histology Using a Multi-Scale, Hierarchical Classification Approach", IEEE Engineering in Medicine and Biology Conference, pp. 4759-62, 2006. (PDF)
20. Madabhushi A, Yang, P, Rosen M, Weinstein S, "Distinguishing Lesions from Posterior Acoustic Shadowing in Breast Ultrasound via Non-Linear Dimensionality Reduction", IEEE Engineering in Medicine and Biology Conference, pp. 3070-73, 2006. (PDF)
19. Wu, Y, Wang, C, Ng, SC, Madabhushi, A, Zhong, YX, "Breast Cancer Diagnosis Using Neural-based Linear Fusion Strategies," Intl. Conference on Neural Information Processing, LNCS. 4234, pp. 165-175, 2006. (PDF)

2005 (top)

18. Madabhushi, A, Metaxas, D, "Ultrasound Techniques in Digital Mammography & Their Application in Breast Cancer Diagnosis", Medical Imaging Systems Technology: Analysis and Computational Methods (World Scientific Publication Co.), pp. 119-150, 2005.
    
17. Madabhushi, A, Udupa, J, "Interplay of Inhomogeneity Correction and Intensity Standardization in MR Image Analysis", IEEE Transactions on Medical Imaging, vol. 24(5), pp. 561-576, 2005. (PDF)
16. Madabhushi, A, Feldman, M, Metaxas, D, Tomasezweski, J, Chute, D, "Automated Detection of Prostatic Adenocarcinoma from High Resolution Ex Vivo MRI", IEEE Transactions on Medical Imaging, Vol. 24(12), pp. 1611-25, 2005.(PDF)
15. Madabhushi, A, Shi, J, Rosen, M, Tomasezweski, J, Feldman, M, "Graph Embedding to Improve Supervised Classification: Detecting Prostate Cancer," in MICCAI, LNCS. 3749, pp. 729-738, 2005. (PDF)
14. Madabhushi, A, Udupa, J, "New Methods of MR Image Intensity Standardization: Use of Generalized Scale", SPIE Medical Imaging, Vol. 5747, pp. 1143-54, 2005. (PDF)
13. Souza, A, Udupa, J, Madabhushi, A, "Generalized scale-based image filtering", SPIE Medical Imaging, Vol. 5747, pp. 732-42, 2005. (PDF)
12. Madabhushi, A, Udupa, J, Souza, A, "Generalized ball scale: theory, algorithms, and application in inhomogeneity correction", SPIE Medical Imaging, Vol. 5747, pp. 1509-20, 2005. (PDF)

2004 (top)

11. Madabhushi, A, Udupa, J, Souza, A, "Generalized Scale: Theory, Algorithms and Application to Inhomogeneity Correction", SPIE Medical Imaging, Vol. 5370, pp. 765-776, 2004.(PDF)
10. Madabhushi, A, "Generalized Scale: Theory, Algorithms, and Applications in Image Analysis", PhD Dissertation, Dept. of Bioengineering, University of Pennsylvania, 2004. (Link)

2003 (top)

9. Madabhushi, A, Metaxas, D, "Combining, Low, High and Empirical Domain Knowledge for Automated Segmentation of Ultrasonic Breast Lesions",IEE Transactions in Medical Imaging, vol. 22(2), pp. 155-169, 2003. (PDF)
8. Madabhushi, A, Feldman, M, Metaxas, D, Chute, D, Tomasezweski, J, "Optimally Combining 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MR Images", IEEE EMBS, pp. 614-17, 2003. (PDF)
7. Madabhushi, A, Feldman, M, Metaxas, D, Chute, D, Tomasezweski, J, "A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High-Resolution MR”, in MICCAI, Vol. 2878, pp. 581-91, 2003. (PDF)

2002 (top)

6. Madabhushi, A, Udupa, J, "Evaluating the effect of Intensity Standardization and Inhomogeneity Correction on Magnetic Resonance Images," 28th IEEE North-East Conference on Bioengineering, pp. 137-138, 2002. (PDF)
5. Madabhushi, A, Metaxas, D, "Automatic Boundary Extraction of Tumors in Ultrasonic Breast Images", IEEE International Symposium on Biomedical Imaging, pp. 601-604, 2002. (PDF)
4. Wei, G-Q, Madabhushi, A, Qian, J, Engdahl, J, "Automatic Quantification of Liver-heart Cross Talk for Quality Assessment in SPECT Myocardial Perfusion Imaging", SPIE Medical Imaging, Vol. 4684, pp. 965-72, 2002. (PDF)

2000 (top)

3. Madabhushi, A, "Using the Movement of the Head to Recognize Human Activity", Masters Thesis, Dept. of Biomedical Engineering, University of Texas at Austin, 2000.
2. Madabhushi, A, and Aggarwal, J. K, "Using Head Movement to Recognize Activity", International Conference on Pattern Recognition, Vol. 4, pp 698-701, (2000). (PDF)

1999 (top)

1. Madabhushi, A, and Aggarwal, J. K, "A Bayesian Approach to Human Activity Recognition", 2nd IEEE   Workshop on Visual Surveillance Systems, pp. 25-32, (1999).(PDF)

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