Publications

Patents:

  • Co-Occurrence of Local Anisotropic Gradient Orientations
    Prasanna, P, Tiwari, P, Madabhushi, A
    USSN: 9,483,822 (November, 2016)
  • Entropy-Based Radiogenomic Descriptors on Magnetic Resonance Imaging (MRI) for Molecular Characterization of Breast Cancer
    Prasanna, P, Braman, N, Singh, S, Madabhushi, A, Harris, L, Varadan, V
    Pending, US Application No: 15/397,266
  • Radiographic-Deformation and Textural Heterogeneity (r-Dep TH): An Integrated Descriptor for Brain Tumor Prognosis
    Prasanna, P, Tiwari, P, Madabhushi, A
    Invention Disclosure filed, Case No: 2017-3239

Journal publications:

  • Beig, N, Patel, J, Prasanna, P, Hill, V, Gupta, A. Correa, R, Bera, K, Singh, S, Partovi, S, Varadan, V, Ahluwalia, M, Madabhushi, A, Tiwari, P, “Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Gioblastoma”, Nature Scientific Reports 2017 (to appear)
  • Thawani, R, McLane, M, Beig, N, Ghose, S, Prasanna, P, Velcheti, V, Madabhushi, A, “Radiomics and Radiogenomics in Lung cancer : A review for the Clinician” , Lung Cancer 2017
  • Bektik, E, Dennis, A, Prasanna, P, Madabhushi, A, Fu, JD, “Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes”, PLoS one 2017
  • Braman, N, Etesami, M, Prasanna, P, Dubchuk, C, Gilmore, H, Tiwari, P, Plecha, D, Madabhushi, A, “DCE-MRI intratumoral and peritumoral radiomics enable pre-treatment prediction of response to neo-adjuvant chemotherapy in breast cancer”, Breast Cancer Research 2017
  • Prasanna, P, Patel, J, Partovi, S, Madabhushi, A, Tiwari, P, “Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in Glioblastoma Multiforme: Preliminary Findings”, European Radiology 2016. Pubmed 
  • Prasanna, P, Tiwari, P, Madabhushi, A, “Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor”, Nature Scientific Reports  2016  Link
  • Tiwari, P, Prasanna, P, Wolansky, L, Pinho, M, Cohen, M, Nayate, AP, Gupta, A, Singh, G, Hatanpaa, K, Sloan, A, Rogers, L, Madabhushi, A, Can Computer-extracted texture features distinguish Radiation Necrosis from Recurrent Brain Tumors on multi-parametric MRI? – A Feasibility Study, American Journal of Neuro Radiology, 2016  (Top 10 most read AJNR papers in 2016) (Nominated for the annual Lucien Levy Best Research Article Award). Link
  • Prasanna, P, Dana, K, Gucunski, N, Basily, B, La, H, Lim, R, Parvardeh, H, “Application of Computer Vision Techniques in Surface Health Monitoring of Concrete Bridges”,  IEEE Trans. on Automated Science and Engineering 2016 (link)

Conference publications:

  • Prasanna, P, Mitra, J, Beig, N, Partovi, S, Singh, G, Pinho, M, Madabhushi, A, Tiwari, P. “Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An integrated descriptor for brain tumor prognosis”, MICCAI 2017
  • Antunes, J, Prasanna, P, Madabhushi, A, Tiwari P, Viswanath S, “RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing intra-tumoral heterogeneity for response and outcome prediction”, MICCAI 2017​
  • Beig, N, Patel, J, Prasanna, P, Partovi, S, Varadan, V, Madabhushi, A, Tiwari, P, “Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in Glioblastoma”, The International Society for Optics and Photonics (SPIE) Medical Imaging, 2017
  • Prasanna, P*, Tiwari, P*, Madabhushi, A, “Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe):  Distinguishing tumor confounders and molecular subtypes on MRI,”  MICCAI 2014. (*joint first authors) (Young Scientist Award, runners up, selected as oral presentation, Acceptance rate = 4%) Pubmed
  • ​Tiwari, P, Prasanna, P, Rogers, L, Wolansky, L,  Badve, C, Cohen, M, Madabhushi, A, “Computerized image analysis of texture descriptors in multi-parametric MRI to distinguish recurrent brain tumor from radiation necrosis”, SPIE Medical Imaging, 2014 (Honorable Mention for Best Poster Presentation, Conference on Computer Aided Diagnosis) Pubmed
  • Prasanna, P, Jain, S, Bhagat, N, Madabhushi, A, “Decision support system for detection of diabetic retinopathy using smartphones”, Pervasive Health 2013 (link)
  • Prasanna, P, Dana, K, Gucunski, N, Basily, B, “Computer-vision based crack detection and analysis”, SPIE Smart Structures 2012 (link)

Peer-reviewed abstracts/posters/demos

  • Prasanna*, P, Ismail*, M,, Huang, R, Singh, G, Thawani, R, Madabhushi, A, Tiwari, P, “Compactness of peritumoral edema on routine MRI appears to distinguish tumor recurrence from pseudo-progression in primary brain tumors: Preliminary findings.” Proceedings of the Radiologic Society of North America (RSNA) 2017.
  • Ismail, M, Prasanna, P, Huang, R, Singh, G, Thawani, R, Madabhushi, A, Aahluwalia, M, Tiwari, P, “Shape attributes of enhancing lesion boundaries can differentiate tumor recurrence from pseudoprogression on routine brain MRI scans: Preliminary findings.” Society of Neuro-oncology (SNO) 2017.
  • Beig, N , Correa, R , Prasanna, P , Mitra, J , Nayate, A , Madabhushi, A , and Tiwari, P, “Radiogenomic analysis of distinct tumor sub-compartments on T2 and FLAIR predict distinct molecular subtypes in Lower Grade Gliomas”, The International Society for Magnetic Resonance in Medicine (ISMRM) 25th Annual Meeting , 2017
  • Prasanna, P, Nayate, A, Gupta, A, Rogers, L,Wolansky, L, Singh, G,  Pinho, M, Hatanpaa, K, Madabhushi, A, Tiwari, P, “Human-Machine Performance Comparison Study in Distinguishing Radiation Necrosis from Brain Tumor Recurrence on Routine MRI”, RSNA 2016.
  • Prasanna, P, Rogers, L, Cohen, M, Singh, G, Badve, C, Wolansky, Madabhushi, A, Tiwari, P, “Computer extracted Texture Descriptors on MRI that Distinguish Radiation, Necrosis and Tumor Recurrence Post-Radiotherapy in Primary Neoplasms are Associated with Vascular, Necrotic and Demyelinating changes”, RSNA 2016.
  • Beig, N, Orooji, M, Rajiah, P, Rakshit, S, Yang, M, Jacono, F, Prasanna, P, Tiwari, P, Velcheti, V, Gilkeson, R, Linden, P, Madabhushi, A, “Radiomic Features of the Perinodular Habitat on Non-contrast Lung CT Discriminates Adenocarcinoma from Granulomas”, RSNA 2016.
  • Beig, N, Correa, R, Prasanna P, Mitra J, Nayate A, Madabhushi A, Tiwari, P, “Predicting IDH mutation status on routine treatment-naïve MRI using radiogenomic features from peritumoral brain parenchyma”, SNO 2016.
  • Prasanna, P, Nayate, A, Gupta, A, Rogers, L, Singh, G, Wolansky, L, Pinho, M, Hatanpaa, K, Madabhushi, A, Tiwari, P, “Distinguishing radiation necrosis from brain tumor recurrence on routine MRI: A preliminary human-machine reader comparison study”, SNO 2016.
  • Prasanna, P, Rogers, L, Cohen, M, Singh, G, Badve, C, Wolansky, Madabhushi, A, Tiwari, P, “Features of local gradient disorder on MRI that distinguish radiation necrosis and tumor recurrence post-radiotherapy are associated with zonal necrosis, vessel wall thickening, hyalinization and demyelination: A preliminary study in brain tumors”, SNO 2016.
  • Prasanna, P, Braman, N, Singh, S, Plecha, D, Gilmore, H, Harris, L, Wan, T, Varadan, V, and Madabhushi, A , “Directional-gradient based radiogenomic descriptors on DCE-MRI appear to distinguish different PAM50-identified subtypes of HER2+ Breast Cancer”, ISMRM  2016
  • Karnawat, A, Prasanna, P, Madabhushi, A, Tiwari, P, “Use of textural radiomic maps in a 3D convolutional neural network framework can augment glioma lesion segmentation”, SNO 2017.
  • Beig, N , Correa, R , Thawani, R , Prasanna, P , Badve, C , Gold, D , DeBlank, P , Tiwari, P. “MRI textural features can differentiate pediatric posterior fossa tumors”, SNO Pediatric Neuro-Oncology Basic and Translational Research Conference, 2017.
  • Prasanna, P, Rose, A, Singh, G, Huang, R, Madabhushi, A and Tiwari, P, “Radiomic features from the necrotic region on post-treatment Gadolinium T1w MRI appear to differentiate pseudo-progression from true tumor progression in primary brain tumors”, ISMRM 2016
  • Prasanna, P , Braman, N, Singh, S, Plecha, D, Gilmore, H, Harris, L, Wan, T, Varadan, V, and Madabhushi, A , “Predicting TP53 mutational status of breast cancers on clinical DCE MRI using directional-gradient based radiogenomic descriptors”, ISMRM 2016 (top 3%).
  • Tiwari, P, Partovi, S, Patel, J, Prasanna, P, Madabhushi, A, “Computer extracted texture descriptors from different tissue compartments within the tumor habitat on treatment-naïve MRI predict clinical survival in glioblastoma patients”, RSNA 2015
  • Tiwari, P, Partovi, S, Patel, J, Prasanna, P, Madabhushi, A, “Computer extracted texture descriptors from different tissue compartments within the tumor habitat on treatment-naïve MRI predict clinical survival in glioblastoma patients”, RSNA 2015
  • Prasanna, P, Tiwari, P, Wolansky, L, Rogers, R, Madabhushi, A, “Morphologic heterogeneity at a pixel-level captured via entropy of gradient orientations on T1-post contrast MRI enables discrimination of tumor recurrence from cerebral radiation necrosis”, SNO 2015
  • Tiwari, P, Prasanna, P, Partovi, S, Patel, J, Madabhushi, A,” Computer extracted texture descriptors from different tissue compartments within the tumor habitat on treatment-naïve MRI predict clinical survival in glioblastoma patients”, SNO 2015
  • Prasanna, P, Tiwari, P, Siddalingappa, A, Lam, T, Wolansky, L, Rogers, R, Madabhushi, A, “Morphologic Study of contrast-enhanced T1-w MRI markers of cerebral radiation necrosis manifested in head-and-neck cancers, primary, and metastatic brain tumors: Preliminary findings”, ISMRM 2015
  • Algohary, A, Viswanath, S, Prasanna, P, Pahwa, S, Gulani, V, Ponsky, L, Stricker, P, Moses, D, Shnier, R, Madabhushi, A, “Quantitative assessment of T2-w MRI to better identify patients with prostate cancer in a screening population”, AUA Annual Meeting, 2015
  • Tiwari, P, Prasanna, P,  Partovi, S, Patel, J, Madabhushi, A, ”Quantitative texture descriptors on baseline MRI can predict patient survival in newly diagnosed GBM patients”, SNO 2014
  • Tiwari, P, Prasanna, P, Wolansky, L, Rogers, R, Madabhushi, A, “Computer-extracted oriented texture features on T1-Gadolinium MRI for distinguishing radiation necrosis from recurrent brain tumors”, SNO 2014
  • Patel, J, Prasanna, P, Partovi, S, Tiwari, P, Madabhushi, A, ”Identifying MRI markers on newly diagnosed Glioblastoma Multiforme to distinguish patients with long and short term survival, BMES Annual Meeting, 2014
  • Tiwari, P, Prasanna, P, Wolansky, L, Rogers, R, Madabhushi, A, “Computerized image analysis of texture descriptors in multi-parametric MRI to distinguish recurrent brain tumor from radiation necrosis”, SNO  2013
  • Prasanna, P, Dana, K, Gucunski, N, Basily, B, “Computer Vision applications in civil engineering”, First Multimedia and Vision Meeting in Greater NY Area, 2012
Advertisements