Pallavi Tiwari

55 papers B 1Journal 19Unranked 33
YearRankTypeTitle / Venue / Authors
2026 J jnl
Agent based web service composition using Q-learning algorithm with puffer fish optimization and petri net model.
J. Ind. Inf. Integr.
Pallavi Tiwari, S. Srinivasan
2025 J jnl
3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer.
CoRR
Hongkun Yu, Syed Jamal Safdar Gardezi, E. Jason Abel, Daniel D. Shapiro, Meghan G. Lubner, Joshua D. Warner, Matthew Smith, Giuseppe Toia, Lu Mao, Pallavi Tiwari, Andrew L. Wentland
2025 — conf
Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI.
ISBI
Hongyi Pan, Gorkem Durak, Zheyuan Zhang, Yavuz Taktak, Elif Keles, Halil Ertugrul Aktas, Alpay Medetalibeyoglu, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Rajesh N. Keswani, Pallavi Tiwari, Candice W. Bolan, Tamas Gonda, Michael G. Gorrins, Michael B. Wallace, Ziyue Xu, Ulas Bagci
2025 — ed.
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
AIPAD/PILM@MICCAI
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
2025 J jnl
Cyst-X: AI-Powered Pancreatic Cancer Risk Prediction from Multicenter MRI in Centralized and Federated Learning.
CoRR
Hongyi Pan, Gorkem Durak, Elif Keles, Deniz Seyithanoglu, Zheyuan Zhang, Alpay Medetalibeyoglu, Halil Ertugrul Aktas, Andrea Mia Bejar, Ziliang Hong, Yavuz Taktak, Gulbiz Dagoglu Kartal, Sukru Mehmet Erturk, Timurhan Cebeci, Maria Jaramillo Gonzalez, Yury Velichko, Lili Zhao, Emil Agarunov, Federica Proietto Salanitri, Concetto Spampinato, Pallavi Tiwari, Ziyue Xu, Sachin Jambawalikar, Ivo G. Schoots, Marco J. Bruno, Chenchan Huang, Candice W. Bolan, Tamas Gonda, Frank H. Miller, Rajesh N. Keswani, Michael B. Wallace, Ulas Bagci
2025 J jnl
Graph-Radiomic Learning (GrRAiL) Descriptor to Characterize Imaging Heterogeneity in Confounding Tumor Pathologies.
CoRR
Dheerendranath Battalapalli, Apoorva Safai, Maria Jaramillo, Hyemin Um, Gustavo Adalfo Pineda Ortiz, Ulas Bagci, Manmeet Ahluwalia, Marwa Ismail, Pallavi Tiwari
2025 — conf
IPMN Risk Assessment Under Federated Learning Paradigm.
ISBI
Hongyi Pan, Ziliang Hong, Gorkem Durak, Elif Keles, Halil Ertugrul Aktas, Yavuz Taktak, Alpay Medetalibeyoglu, Zheyuan Zhang, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Pallavi Tiwari, Candice W. Bolan, Tamas Gonda, Frank H. Miller, Rajesh N. Keswani, Michael B. Wallace, Ziyue Xu, Ulas Bagci
2025 J jnl
Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.
Medical Image Anal.
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
2024 J jnl
Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI.
CoRR
Hongyi Pan, Gorkem Durak, Zheyuan Zhang, Yavuz Taktak, Elif Keles, Ertugrul Aktas, Alpay Medetalibeyoglu, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Rajesh N. Keswani, Pallavi Tiwari, Candice W. Bolan, Tamas Gonda, Michael G. Goggins, Michael B. Wallace, Ziyue Xu, Ulas Bagci
2024 — conf
Graph-Radiomics Learning (GrRAiL): Application to Distinguishing Glioblastoma Recurrence from Pseudo-Progression on Structural MRI.
ISBI
Dheerendranath Battalapalli, Apoorva Safai, Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Raymond Y. Huang, Manmeet Ahluwalia, Pallavi Tiwari
2024 — conf
Human-in-the-Loop (HITL) Learning for Identifying Glioblastoma Hallmarks on H&E Slides.
ISBI
Alvaro A. Sandino, Olivia Krebs, David Becerra, Nelly J. Sandino, Jeffrey Helgager, Eduardo Romero, Pallavi Tiwari
2024 J jnl
IPMN Risk Assessment under Federated Learning Paradigm.
CoRR
Hongyi Pan, Ziliang Hong, Gorkem Durak, Elif Keles, Halil Ertugrul Aktas, Yavuz Taktak, Alpay Medetalibeyoglu, Zheyuan Zhang, Yury Velichko, Concetto Spampinato, Ivo Schoots, Marco J. Bruno, Pallavi Tiwari, Candice W. Bolan, Tamas Gonda, Frank H. Miller, Rajesh N. Keswani, Michael B. Wallace, Ziyue Xu, Ulas Bagci
2024 J jnl
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning.
CoRR
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
2024 — ed.
Machine Learning for Multimodal Healthcare Data - First International Workshop, ML4MHD 2023, Honolulu, Hawaii, USA, July 29, 2023, Proceedings
ML4MHD
Andreas K. Maier, Julia A. Schnabel, Pallavi Tiwari, Oliver Stegle
2024 — conf
Multi-Scale Co-Attention Transformer Model to Integrate Radiology, Histology, and Genomics: Application to Survival Prediction in Glioblastoma.
ISBI
Olivia Krebs, Pallavi Tiwari
2024 J jnl
ResNCT: A Deep Learning Model for the Synthesis of Nephrographic Phase Images in CT Urography.
CoRR
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
2023 — conf
Self-supervised deep learning to predict molecular markers from routine histopathology slides for high-grade glioma tumors.
Digital and Computational Pathology
Olivia Krebs, Shobhit Agarwal, Pallavi Tiwari
2022 — conf
A hierarchical deep learning approach for segmentation of glioblastoma tumor niches on digital histopathology.
Digital and Computational Pathology
Alvaro Sandino Garzon, Ruchika Verma, Yijang Chen, David Becerra Tovar, Eduardo Romero Castro, Pallavi Tiwari
2022 — conf
A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors.
Computer-Aided Diagnosis
Ipsa Yadav, Marwa Ismail, Volodymyr Statsevych, Virginia B. Hill, Ramon Correa, Manmeet Ahluwalia, Pallavi Tiwari
2022 — conf
Multiclass Classification of Disease Using CNN and SVM of Medical Imaging.
ICACDS (2)
Pallavi Tiwari, Deepak Upadhyay, Bhaskar Pant, Noor Mohd
2022 J jnl
RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment.
IEEE J. Biomed. Health Informatics
Jacob T. Antunes, Marwa Ismail, Imran Hossain, Zhoumengdi Wang, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath
2022 J jnl
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.
IEEE Trans. Medical Imaging
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
2021 J jnl
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.
CoRR
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
2020 — conf
"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors.
Computer-Aided Diagnosis
Ramon Correa, Qiu Lei, Jonathan Chen, Johnathan Zeng, Jennifer Yu, Pallavi Tiwari
2020 J jnl
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study.
Frontiers Comput. Neurosci.
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
2020 J jnl
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study.
CoRR
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
2020 — conf
Combining deep and hand-crafted MRI features for identifying sex-specific differences in autism spectrum disorder versus controls.
Computer-Aided Diagnosis
Yashas Hiremath, Marwa Ismail, Ruchika Verma, Jacob Antunes, Pallavi Tiwari
2020 J jnl
MRQy: An Open-Source Tool for Quality Control of MR Imaging Data.
CoRR
Amir Reza Sadri, Andrew Janowczyk, Ren Zou, Ruchika Verma, Jacob Antunes, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath
2020 — conf
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI.
MICCAI (2)
Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari
2020 J jnl
Spatial-And-Context aware (SpACe) "virtual biopsy" radiogenomic maps to target tumor mutational status on structural MRI.
CoRR
Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma, Anas Saeed Bamashmos, Niha G. Beig, Jacob Antunes, Prateek Prasanna, Volodymyr Statsevych, Manmeet Ahluwalia, Pallavi Tiwari
2019 — conf
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.
Computer-Aided Diagnosis
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
2019 — conf
Opportunities and Advances in Radiomics and Radiogenomics in Neuro-Oncology.
RNO-AI@MICCAI
Kaustav Bera, Niha G. Beig, Pallavi Tiwari
2019 — conf
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways.
Computer-Aided Diagnosis
Niha G. Beig, Prateek Prasanna, Virginia B. Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari
2019 — conf
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma.
Computer-Aided Diagnosis
Ruchika Verma, Ramon Correa, Virginia B. Hill, Niha G. Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari
2019 — conf
STructural Rectal Atlas Deformation (StRAD) Features for Characterizing Intra- and Peri-wall Chemoradiation Response on MRI.
MICCAI (4)
Jacob Antunes, ZhouPing Wei, Charlems Álvarez Jimenez, Eduardo Romero, Marwa Ismail, Anant Madabhushi, Pallavi Tiwari, Satish E. Viswanath
2017 J jnl
Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases.
BMC Medical Imaging
Satish Viswanath, Pallavi Tiwari, George Lee, Anant Madabhushi
2017 — conf
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction.
MICCAI (2)
Jacob Antunes, Prateek Prasanna, Anant Madabhushi, Pallavi Tiwari, Satish Viswanath
2017 — conf
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma.
Computer-Aided Diagnosis
Niha G. Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari
2017 — conf
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis.
MICCAI (2)
Prateek Prasanna, Jhimli Mitra, Niha G. Beig, Sasan Partovi, Gagandeep Singh, Marco Pinho, Anant Madabhushi, Pallavi Tiwari
2014 — conf
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI.
MICCAI (3)
Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi
2014 — conf
Identifying MRI markers to evaluate early treatment-related changes post-laser ablation for cancer pain management.
Image-Guided Procedures
Pallavi Tiwari, Shabbar Danish, Anant Madabhushi
2014 — conf
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI.
Computer-Aided Diagnosis
Pallavi Tiwari, Prateek Prasanna, Lisa Rogers, Leo Wolansky, Chaitra Badve, Andrew Sloan, Mark Cohen, Anant Madabhushi
2013 J jnl
Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS.
Medical Image Anal.
Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi
2013 — conf
Quantitative evaluation of multi-parametric MR imaging marker changes post-laser interstitial ablation therapy (LITT) for epilepsy.
Image-Guided Procedures
Pallavi Tiwari, Shabbar Danish, Stephen Wong, Anant Madabhushi
2011 J jnl
A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation.
Medical Image Anal.
Robert Toth, Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi
2011 — conf
CADOnc ©: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI.
ISBI
Satish Viswanath, Pallavi Tiwari, Jonathan Chappelow, Robert Toth, John Kurhanewicz, Anant Madabhushi
2011 — conf
Multi-modal data fusion schemes for integrated classification of imaging and non-imaging biomedical data.
ISBI
Pallavi Tiwari, Satish Viswanath, George Lee, Anant Madabhushi
2011 — conf
Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading.
Prostate Cancer Imaging
Shoshana Ginsburg, Pallavi Tiwari, John Kurhanewicz, Anant Madabhushi
2011 — conf
Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate.
Prostate Cancer Imaging
Pallavi Tiwari, Satish Viswanath, John Kurhanewicz, Anant Madabhushi
2010 — conf
Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy.
MICCAI (3)
Pallavi Tiwari, John Kurhanewicz, Mark Rosen, Anant Madabhushi
2009 — conf
Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data.
MICCAI (1)
Pallavi Tiwari, Mark Rosen, Galen Reed, John Kurhanewicz, Anant Madabhushi
2008 — conf
A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging.
Computer-Aided Diagnosis
Satish Viswanath, Pallavi Tiwari, Mark Rosen, Anant Madabhushi
2008 B conf
A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models.
Image Processing
Robert Toth, Pallavi Tiwari, Mark Rosen, Arjun Kalyanpur, Sona Pungavkar, Anant Madabhushi
2008 — conf
Consensus-Locally Linear Embedding (C-LLE): Application to Prostate Cancer Detection on Magnetic Resonance Spectroscopy.
MICCAI (2)
Pallavi Tiwari, Mark Rosen, Anant Madabhushi
2007 — conf
A Hierarchical Unsupervised Spectral Clustering Scheme for Detection of Prostate Cancer from Magnetic Resonance Spectroscopy (MRS).
MICCAI (2)
Pallavi Tiwari, Anant Madabhushi, Mark Rosen