Prateek Prasanna
Orcid: 0000-0002-3068-3573
According to our database1,
Prateek Prasanna
authored at least 74 papers
between 2013 and 2024.
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Bibliography
2024
Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.
Medical Image Anal., 2024
Data distillation in computational pathology by choosing few representants of the original variance: A use case in ovarian cancer.
Expert Syst. Appl., 2024
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models.
CoRR, 2024
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment.
CoRR, 2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging.
Proceedings of the Topology- and Graph-Informed Imaging Informatics, 2024
MetaStain: Stain-Generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023
Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the Information Processing in Medical Imaging, 2023
Proceedings of the Information Processing in Medical Imaging, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the CENTERIS 2023 - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist, 2023
2022
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.
IEEE Trans. Medical Imaging, 2022
RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment.
IEEE J. Biomed. Health Informatics, 2022
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers.
CoRR, 2022
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network.
CoRR, 2022
Brain Cancer Survival Prediction on Treatment-na ive MRI using Deep Anchor Attention Learning with Vision Transformer.
CoRR, 2022
Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs.
CoRR, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Clinical outcome prediction in COVID-19 using self-supervised vision transformer representations.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022
Brain Cancer Survival Prediction on Treatment-Naïve MRI using Deep Anchor Attention Learning with Vision Transformer.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
Proceedings of the 10th IEEE International Conference on Healthcare Informatics, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification.
Proceedings of the Computer Vision - ECCV 2022, 2022
Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
Imaging Features of Vessels and Leakage Patterns Predict Extended Interval Aflibercept Dosing Using Ultra-Widefield Angiography in Retinal Vascular Disease: Findings From the PERMEATE Study.
IEEE Trans. Biomed. Eng., 2021
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers.
Medical Image Anal., 2021
Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Attention Based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Attention-Based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findings.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
Predicting Mutation Status and Recurrence Free Survival in Non-Small Cell Lung Cancer: A Hierarchical ct Radiomics - Deep Learning Approach.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
Proceedings of the Information Processing in Medical Imaging, 2021
Radiologically Defined Tumor-habitat Adjacency as a Prognostic Biomarker in Glioblastoma.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
2020
Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study.
Frontiers Comput. Neurosci., 2020
Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study.
CoRR, 2020
Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study.
CoRR, 2020
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020
2019
A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
2018
Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2016
2014
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014
2013
Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, 2013