Wang, Z., Cruz-Roa, A., Basavanhally, A., Gilmore, H., Shih, N., Feldman, M., ... Madabhushi, A.(2014).Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.. Journal of medical imaging (Bellingham, Wash.), 1(3), 034003.
Rusu, M., Bloch, B., Jaffe, C., Genega, E., Lenkinski, R., Rofsky, N., ... Madabhushi, A.(2014).Prostatome: a combined anatomical and disease based MRI atlas of the prostate.. Medical physics, 41(7), 072301.
Agner, S., Rosen, M., Englander, S., Tomaszewski, J., Feldman, M., Zhang, P., ... Madabhushi, A.(2014).Computerized image analysis for identifying triple-negative breast cancers and differentiating them from other molecular subtypes of breast cancer on dynamic contrast-enhanced MR images: a feasibility study.. Radiology, 272(1), 91-9.
Lee, G., Sparks, R., Karabalin, R., Shih, N., Feldman, M., Spangler, E., ... Madabhushi, A.(2014).Co-occurring gland angularity in localized subgraphs: predicting biochemical recurrence in intermediate-risk prostate cancer patients.. PloS one, 9(5), e97954.
Viswanath, S. E., Toth, R., Rusu, M., Sperling, D., Lepor, H., Futterer, J., ... Madabhushi, A.(2014).Identifying Quantitative In Vivo Multi-Parametric MRI Features For Treatment Related Changes after Laser Interstitial Thermal Therapy of Prostate Cancer. Neurocomputing,().
Wang, X., Madabhushi, A., Phinikaridou, A., Hamilton, J., Huang, R., Pham, T., ... Buckler, A.(2014).Spatio-temporal texture (SpTeT) for distinguishing vulnerable from stable atherosclerotic plaque on dynamic contrast enhancement (DCE) MRI in a rabbit model.. Medical physics, 41(4), 042303.
Wang, X., Madabhushi, A., Phinikaridou, A., Hamilton, J., Huang, R., Pham, T., ... Buckler, A.(2014).Spatio-temporal texture (SpTeT) for distinguishing vulnerable from stable atherosclerotic plaque on dynamic contrast enhancement (DCE) MRI in a rabbit model.. Medical physics, 41(4), 042303.
Madabhushi, A., Ginsburg, S., Rusu, M., & Kurhanewicz, J.(2014).Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 903509, 9035(), 13 pages. DOI: 10.1117/12.2043937
Madabhushi, A., , E., Rusu, M., Karthigeyan, S., Agner, S., Sparks, R., ... Feldman, M.(2014).Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI. SPIE 9034, Medical Imaging 2014: Image Processing, 90343P,(), 15 pages. DOI: 10.1117/12.2044317
Madabhushi, A., Cruz-Roa, A., Basavanhally, A., Gonzalez, F., Gilmore, H., Feldman, M., ... Tomaszewski, J.(2014).Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 904103, 9041(), 15 pages. DOI: 10.1117/12.2043872
Madabhushi, A., Wang, H., Cruz-Roa, A., Basavanhally, A., Gilmore, H., Shih, N., ... Gonzalez, F.(2014).Cascaded ensemble of convolutional neural networks and handcrafted features for mitosis detection. Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 90410B , 9041(), 10 pages. DOI: 10.1117/12.2043902
Madabhushi, A., Litgens, G., Elliott, R., Shih, N., Feldman, M., Barentsz, J., ... Huisman, H.(2014).Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI. SPIE Proceedings, 9035(), 14 pages. DOI: 10.1117/12.2043751
Tiwari, P., Danish, S., & Madabhushi, A.(2014).Identifying MRI markers to evaluate early treatment related changes post laser ablation for cancer pain management.. Proceedings of SPIE--the International Society for Optical Engineering, 9036(), 90362L.
Agner, S., Rosen, M., Englander, S., Tomaszewski, J., Feldman, M., Zhang, P., ... Madabhushi, A.(2014).Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study.. Radiology,(), 121031.
Litjens, G., Toth, R., Van de Ven, W., Hoeks, C., Kerkstra, S., Van Ginneken, B., ... Madabhushi, A.(2014).Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.. Medical image analysis, 18(2), 359-73.
Litjens, G., Toth, R., Van de Ven, W., Hoeks, C., Kerkstra, S., Van Ginneken, B., ... Madabhushi, A.(2014).Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.. Medical image analysis, 18(2), 359-73.
Prasanna, P., Tiwari, P., & Madabhushi, A.(2014).Co-occurrence of local anisotropic gradient orientations (CoLIAGe): distinguishing tumor confounders and molecular subtypes on MRI.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 17(Pt 3), 73-80.
Wang, Z., Singanamalli, A., Ginsburg, S., & Madabhushi, A.(2014).Selecting features with group-sparse nonnegative supervised canonical correlation analysis: multimodal prostate cancer prognosis.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 17(Pt 3), 385-92.
Tiwari, P., Danish, S., & Madabhushi, A.(2014).Identifying MRI markers to evaluate early treatment related changes post laser ablation for cancer pain management. SPIE Medical Imaging,().
