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ORCIDPallavi Tiwari
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2020 – today
- 2025
[e2]Federica Proietto Salanitri
, Serestina Viriri, Ulas Bagci, Pallavi Tiwari, Boqing Gong, Concetto Spampinato, Simone Palazzo, Giovanni Bellitto, Nancy Zlatintsi, Panagiotis Paraskevas Filntisis, Cecilia S. Lee, Aaron Y. Lee:
Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine - First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Lecture Notes in Computer Science 15197, Springer 2025, ISBN 978-3-031-73482-3 [contents]- 2024
- [c30]Dheerendranath Battalapalli, Apoorva Safai, Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Raymond Huang, Manmeet Ahluwalia, Pallavi Tiwari:
Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI. ISBI 2024: 1-5 - [c29]Olivia Krebs, Pallavi Tiwari:
Multi-Scale Co-Attention Transformer Model to Integrate Radiology, Histology, and Genomics: Application to Survival Prediction in Glioblastoma. ISBI 2024: 1-4 - [c28]Alvaro A. Sandino, Olivia Krebs, David Becerra, Nelly J. Sandino, Jeffrey Helgager, Eduardo Romero, Pallavi Tiwari:
Human-in-the-Loop (HITL) Learning for Identifying Glioblastoma Hallmarks on H&E Slides. ISBI 2024: 1-4 - [e1]Andreas K. Maier, Julia A. Schnabel, Pallavi Tiwari, Oliver Stegle:
Machine Learning for Multimodal Healthcare Data - First International Workshop, ML4MHD 2023, Honolulu, Hawaii, USA, July 29, 2023, Proceedings. Lecture Notes in Computer Science 14315, Springer 2024, ISBN 978-3-031-47678-5 [contents] - [i6]Syed Jamal Safdar Gardezi, Lucas Aronson, Peter Wawrzyn, Hongkun Yu, E. Jason Abel, Daniel D. Shapiro, Meghan G. Lubner, Joshua D. Warner, Giuseppe Toia, Lu Mao, Pallavi Tiwari, Andrew L. Wentland:
ResNCT: A Deep Learning Model for the Synthesis of Nephrographic Phase Images in CT Urography. CoRR abs/2405.04629 (2024) - [i5]Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros, Pallavi Tiwari, Derk C. F. Klatte, Megan Engels, Sanne Hoogenboom, Candice W. Bolan, Emil Agarunov, Nassier Harfouch, Chenchan Huang, Marco J. Bruno, Ivo Schoots, Rajesh N. Keswani, Frank H. Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Baris Turkbey, Michael B. Wallace, Ulas Bagci:
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning. CoRR abs/2405.12367 (2024) - 2022
- [j6]Jacob T. Antunes, Marwa Ismail, Imran Hossain, Zhoumengdi Wang, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. IEEE J. Biomed. Health Informatics 26(6): 2627-2636 (2022) - [j5]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. IEEE Trans. Medical Imaging 41(7): 1764-1777 (2022) - [c27]Pallavi Tiwari, Deepak Upadhyay, Bhaskar Pant, Noor Mohd:
Multiclass Classification of Disease Using CNN and SVM of Medical Imaging. ICACDS (2) 2022: 88-99 - [c26]Ipsa Yadav, Marwa Ismail, Volodymyr Statsevych, Virginia B. Hill, Ramon Correa, Manmeet Ahluwalia, Pallavi Tiwari:
A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors. Medical Imaging: Computer-Aided Diagnosis 2022 - 2021
- [i4]Marwa Ismail, Prateek Prasanna, Kaustav Bera, Volodymyr Statsevych, Virginia B. Hill, Gagandeep Singh, Sasan Partovi, Niha G. Beig, Sean D. McGarry, Peter S. LaViolette, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma. CoRR abs/2103.07423 (2021) - 2020
- [j4]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Manmeet Ahluwalia, Anant Madabhushi, Pallavi Tiwari:
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. Frontiers Comput. Neurosci. 14: 563439 (2020) - [c25]Ramon Correa, Qiu Lei, Jonathan Chen, Johnathan Zeng, Jennifer Yu, Pallavi Tiwari:
"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors. Medical Imaging: Computer-Aided Diagnosis 2020 - [c24]Yashas Hiremath, Marwa Ismail, Ruchika Verma, Jacob Antunes, Pallavi Tiwari:
Combining deep and hand-crafted MRI features for identifying sex-specific differences in autism spectrum disorder versus controls. Medical Imaging: Computer-Aided Diagnosis 2020 - [c23]Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari:
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. MICCAI (2) 2020: 305-314 - [i3]Amir Reza Sadri, Andrew Janowczyk, Ren Zou, Ruchika Verma, Jacob Antunes, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
MRQy: An Open-Source Tool for Quality Control of MR Imaging Data. CoRR abs/2004.04871 (2020) - [i2]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna, Gagandeep Singh, Kaustav Bera, Rajat Thawani, Anant Madabhushi, Manmeet Ahluwalia, Pallavi Tiwari:
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. CoRR abs/2006.09483 (2020) - [i1]Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari:
Spatial-And-Context aware (SpACe) "virtual biopsy" radiogenomic maps to target tumor mutational status on structural MRI. CoRR abs/2006.09878 (2020)
2010 – 2019
- 2019
- [c22]Ruchika Verma, Ramon Correa, Virginia B. Hill, Niha G. Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari:
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. Medical Imaging: Computer-Aided Diagnosis 2019: 109500B - [c21]Niha G. Beig, Prateek Prasanna, Virginia B. Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. Medical Imaging: Computer-Aided Diagnosis 2019: 109501B - [c20]Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha G. Beig, Kaustav Bera, Volodymyr Statsevych, Alexander R. Judkins, Anant Madabhushi, Pallavi Tiwari:
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Medical Imaging: Computer-Aided Diagnosis 2019: 109501E - [c19]Kaustav Bera, Niha G. Beig, Pallavi Tiwari:
Opportunities and Advances in Radiomics and Radiogenomics in Neuro-Oncology. RNO-AI@MICCAI 2019: 12-23 - [c18]Jacob Antunes, Zhouping Wei, Charlems Álvarez Jimenez, Eduardo Romero, Marwa Ismail, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath:
STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI. MICCAI (4) 2019: 611-619 - 2017
- [j3]Satish Viswanath, Pallavi Tiwari, George Lee, Anant Madabhushi:
Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases. BMC Medical Imaging 17(1): 2:1-2:17 (2017) - [c17]Niha G. Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Medical Imaging: Computer-Aided Diagnosis 2017: 101341U - [c16]Prateek Prasanna, Jhimli Mitra, Niha G. Beig, Sasan Partovi, Gagandeep Singh, Marco Pinho, Anant Madabhushi, Pallavi Tiwari:
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. MICCAI (2) 2017: 459-467 - [c15]Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath:
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. MICCAI (2) 2017: 468-476 - 2014
- [c14]Pallavi Tiwari, Prateek Prasanna, Lisa Rogers, Leo Wolansky, Chaitra Badve, Andrew Sloan, Mark Cohen, Anant Madabhushi:
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. Medical Imaging: Computer-Aided Diagnosis 2014: 90352B - [c13]Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi:
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. MICCAI (3) 2014: 73-80 - [c12]Pallavi Tiwari, Shabbar Danish, Anant Madabhushi:
Identifying MRI markers to evaluate early treatment-related changes post-laser ablation for cancer pain management. Medical Imaging: Image-Guided Procedures 2014: 90362L - 2013
- [j2]Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi:
Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS. Medical Image Anal. 17(2): 219-235 (2013) - [c11]Pallavi Tiwari, Shabbar Danish, Stephen Wong, Anant Madabhushi:
Quantitative evaluation of multi-parametric MR imaging marker changes post-laser interstitial ablation therapy (LITT) for epilepsy. Medical Imaging: Image-Guided Procedures 2013: 86711Y - 2011
- [j1]Robert Toth, Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi:
A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation. Medical Image Anal. 15(2): 214-225 (2011) - [c10]Pallavi Tiwari, Satish Viswanath, George Lee, Anant Madabhushi:
Multi-modal data fusion schemes for integrated classification of imaging and non-imaging biomedical data. ISBI 2011: 165-168 - [c9]Satish Viswanath, Pallavi Tiwari, Jonathan Chappelow, Robert Toth, John Kurhanewicz, Anant Madabhushi:
CADOnc ©: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI. ISBI 2011: 2095-2098 - [c8]Pallavi Tiwari, Satish Viswanath, John Kurhanewicz, Anant Madabhushi:
Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate. Prostate Cancer Imaging 2011: 80-91 - [c7]Shoshana Ginsburg, Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi:
Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading. Prostate Cancer Imaging 2011: 146-157 - 2010
- [c6]Pallavi Tiwari, John Kurhanewicz, Mark Rosen, Anant Madabhushi:
Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy. MICCAI (3) 2010: 666-673
2000 – 2009
- 2009
- [c5]Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Anant Madabhushi:
Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data. MICCAI (1) 2009: 844-851 - 2008
- [c4]Satish Viswanath, Pallavi Tiwari, Mark Rosen, Anant Madabhushi:
A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging. Medical Imaging: Computer-Aided Diagnosis 2008: 69153D - [c3]Pallavi Tiwari, Mark Rosen, Anant Madabhushi:
Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy. MICCAI (2) 2008: 330-338 - [c2]Robert Toth, Pallavi Tiwari, Mark Rosen, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi:
A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models. Medical Imaging: Image Processing 2008: 69144S - 2007
- [c1]Pallavi Tiwari, Anant Madabhushi, Mark Rosen:
A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS). MICCAI (2) 2007: 278-286
Coauthor Index
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