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Prateek Prasanna
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2020 – today
- 2024
- [j8]Jennifer Salguero
, Prateek Prasanna, Germán Corredor
Data distillation in computational pathology by choosing few representants of the original variance: A use case in ovarian cancer. Expert Syst. Appl. 245: 123028 (2024) - [j7]Saarthak Kapse
Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning. Medical Image Anal. 93: 103070 (2024) - [c56]Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel H. Saltz, Dimitris Samaras:
Learned Representation-Guided Diffusion Models for Large-Image Generation. CVPR 2024: 8532-8542 - [c55]Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna:
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. CVPR 2024: 11226-11237 - [c54]Paras Goel, Saarthak Kapse, Pushpak Pati, Prateek Prasanna:
Coca-Mil: Attention-Based Handcrafted-Deep Feature Fusion in Computational Pathology. ISBI 2024: 1-5 - [c53]Meiliong Xu, Nate Anderson, Richard M. Levenson, Prateek Prasanna, Chao Chen:
A Topological Comparison of the Fluorescence Imitating Brightfield Imaging and H&E Imaging. TGI3@MICCAI 2024: 122-133 - [c52]Wentao Huang, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Chao Chen:
Hard Negative Sample Mining for Whole Slide Image Classification. MICCAI (4) 2024: 144-154 - [c51]Aishik Konwer, Prateek Prasanna:
MetaStain: Stain-Generalizable Meta-learning for Cell Segmentation and Classification with Limited Exemplars. MICCAI (4) 2024: 307-317 - [c50]Joseph Bae
HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images. MICCAI (5) 2024: 317-327 - [c49]Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Joel H. Saltz, Chao Chen:
Semi-supervised Contrastive VAE for Disentanglement of Digital Pathology Images. MICCAI (4) 2024: 459-469 - [c48]Srikar Yellapragada, Alexandros Graikos, Prateek Prasanna, Tahsin M. Kurç, Joel H. Saltz, Dimitris Samaras:
PathLDM: Text conditioned Latent Diffusion Model for Histopathology. WACV 2024: 5170-5179 - [i33]Xuan Xu, Saarthak Kapse, Prateek Prasanna:
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment. CoRR abs/2408.15218 (2024) - [i32]Moinak Bhattacharya, Gagandeep Singh, Shubham Jain, Prateek Prasanna:
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models. CoRR abs/2410.00307 (2024) - [i31]Wentao Huang, Xiaoling Hu, Shahira Abousamra, Prateek Prasanna, Chao Chen:
Hard Negative Sample Mining for Whole Slide Image Classification. CoRR abs/2410.02212 (2024) - 2023
- [c47]Yunfan Li, Himanshu Gupta, Prateek Prasanna, I. V. Ramakrishnan, Haibin Ling:
Surgical Phase Recognition in Laparoscopic Cholecystectomy. CENTERIS/ProjMAN/HCist 2023: 2006-2012 - [c46]Aishik Konwer, Xiaoling Hu, Joseph Bae, Xuan Xu, Chao Chen, Prateek Prasanna
Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. ICCV 2023: 21358-21368 - [c45]Yunfan Li, Himanshu Gupta, Haibin Ling, I. V. Ramakrishnan, Prateek Prasanna, Georgios Georgakis, Aaron Sasson:
Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy. ICHI 2023: 330-337 - [c44]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. ICLR 2023 - [c43]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Token Sparsification for Faster Medical Image Segmentation. IPMI 2023: 743-754 - [c42]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras:
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. IPMI 2023: 783-794 - [c41]Saarthak Kapse, Srijan Das
CD-Net: Histopathology Representation Learning Using Context-Detail Transformer Network. ISBI 2023: 1-5 - [c40]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna
Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation. ISBI 2023: 1-6 - [c39]Moinak Bhattacharya, Prateek Prasanna:
Audio-visual feature fusion for improved thoracic disease classification. Medical Imaging: Computer-Aided Diagnosis 2023 - [c38]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-Driven Diffusion Autoencoder for Histopathology Image Analysis. DGM4MICCAI 2023: 66-76 - [c37]Jingwei Zhang
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. ISIC/Care-AI/MedAGI/DeCaF@MICCAI 2023: 161-170 - [c36]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel H. Saltz, Maria Vakalopoulou, Dimitris Samaras:
Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning. MICCAI (8) 2023: 624-634 - [c35]Aishik Konwer, Chao Chen, Prateek Prasanna:
MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities. MLMI@MICCAI (1) 2023: 361-371 - [c34]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. NeurIPS 2023 - [i30]Aishik Konwer, Xiaoling Hu, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna:
Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation. CoRR abs/2302.04308 (2023) - [i29]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Token Sparsification for Faster Medical Image Segmentation. CoRR abs/2303.06522 (2023) - [i28]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Joel H. Saltz, Maria Vakalopoulou, Dimitris Samaras:
Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning. CoRR abs/2303.12214 (2023) - [i27]Xuan Xu, Saarthak Kapse, Rajarsi Gupta, Prateek Prasanna:
ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis. CoRR abs/2304.01053 (2023) - [i26]Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen:
Topology-Aware Uncertainty for Image Segmentation. CoRR abs/2306.05671 (2023) - [i25]Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel H. Saltz, Maria Vakalopoulou, Prateek Prasanna, Dimitris Samaras:
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology. CoRR abs/2307.09570 (2023) - [i24]Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna, Chao Chen:
Learning to Segment from Noisy Annotations: A Spatial Correction Approach. CoRR abs/2308.02498 (2023) - [i23]Srikar Yellapragada, Alexandros Graikos, Prateek Prasanna, Tahsin M. Kurç, Joel H. Saltz, Dimitris Samaras:
PathLDM: Text conditioned Latent Diffusion Model for Histopathology. CoRR abs/2309.00748 (2023) - [i22]Saarthak Kapse, Srijan Das, Jingwei Zhang, Rajarsi R. Gupta, Joel H. Saltz, Dimitris Samaras, Prateek Prasanna:
Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning. CoRR abs/2309.06439 (2023) - [i21]Yunfan Li, Himanshu Gupta, Haibin Ling, I. V. Ramakrishnan, Prateek Prasanna, Georgios Georgakis, Aaron Sasson:
Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy. CoRR abs/2309.07330 (2023) - [i20]Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna
Learned representation-guided diffusion models for large-image generation. CoRR abs/2312.07330 (2023) - [i19]Saarthak Kapse, Pushpak Pati, Srijan Das, Jingwei Zhang, Chao Chen, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras, Rajarsi R. Gupta, Prateek Prasanna
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology. CoRR abs/2312.15010 (2023) - 2022
- [j6]Jacob T. Antunes
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
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) - [c33]Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna:
Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. CVPR 2022: 18802-18813 - [c32]Moinak Bhattacharya
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification. ECCV (21) 2022: 679-698 - [c31]Saumya Gupta
Learning Topological Interactions for Multi-Class Medical Image Segmentation. ECCV (29) 2022: 701-718 - [c30]Ibrahim Hammoud, Prateek Prasanna, I. V. Ramakrishnan, Adam Singer, Mark Henry, Henry C. Thode:
EventScore: An Automated Real-time Early Warning Score for Clinical Events. ICHI 2022: 192-200 - [c29]Saarthak Kapse, Luke Torre-Healy, Richard A. Moffitt, Rajarsi Gupta, Prateek Prasanna:
Subtype-Specific Spatial Descriptors of Tumor-Immune Microenvironment are Prognostic of Survival in Lung Adenocarcinoma. ISBI 2022: 1-5 - [c28]Xuan Xu, Prateek Prasanna:
Brain Cancer Survival Prediction on Treatment-Naïve MRI using Deep Anchor Attention Learning with Vision Transformer. ISBI 2022: 1-5 - [c27]Aishik Konwer, Prateek Prasanna:
Clinical outcome prediction in COVID-19 using self-supervised vision transformer representations. Medical Imaging: Computer-Aided Diagnosis 2022 - [c26]Moinak Bhattacharya
GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework. MICCAI (3) 2022: 686-696 - [i18]Lei Zhou, Joseph Bae, Huidong Liu, Gagandeep Singh, Jeremy Green, Amit Gupta, Dimitris Samaras, Prateek Prasanna:
Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs. CoRR abs/2201.07344 (2022) - [i17]Xuan Xu, Prateek Prasanna:
Brain Cancer Survival Prediction on Treatment-na ive MRI using Deep Anchor Attention Learning with Vision Transformer. CoRR abs/2202.01857 (2022) - [i16]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classification. CoRR abs/2202.11781 (2022) - [i15]Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna
Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. CoRR abs/2203.01933 (2022) - [i14]Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Self Pre-training with Masked Autoencoders for Medical Image Analysis. CoRR abs/2203.05573 (2022) - [i13]Saarthak Kapse, Srijan Das, Prateek Prasanna:
CD-Net: Histopathology Representation Learning using Pyramidal Context-Detail Network. CoRR abs/2203.15078 (2022) - [i12]Yunfan Li, Vinayak Shenoy, Prateek Prasanna, I. V. Ramakrishnan, Haibin Ling, Himanshu Gupta:
Surgical Phase Recognition in Laparoscopic Cholecystectomy. CoRR abs/2206.07198 (2022) - [i11]Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin
Learning Topological Interactions for Multi-Class Medical Image Segmentation. CoRR abs/2207.09654 (2022) - [i10]Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta
Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. CoRR abs/2210.02273 (2022) - [i9]Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras:
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. CoRR abs/2212.12105 (2022) - 2021
- [j4]Cheng Lu
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. 68: 101903 (2021) - [j3]Azam Moosavi
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. 68(6): 1777-1786 (2021) - [c25]Xuan Xu, Dimitris Samaras, Prateek Prasanna:
Radiologically Defined Tumor-habitat Adjacency as a Prognostic Biomarker in Glioblastoma. EMBC 2021: 3998-4001 - [c24]Fan Wang
TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. IPMI 2021: 386-397 - [c23]Divek Patel, Connor Cowan, Prateek Prasanna:
Predicting Mutation Status and Recurrence Free Survival in Non-Small Cell Lung Cancer: A Hierarchical ct Radiomics - Deep Learning Approach. ISBI 2021: 882-885 - [c22]Connor Cowan, Joseph Bae, Gagandeep Singh, Rohit Khullar, Shrey Shah, Nikhil Madan, Prateek Prasanna:
Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findings. Medical Imaging: Computer-Aided Diagnosis 2021 - [c21]Lei Zhou, Joseph Bae, Huidong Liu, Gagandeep Singh, Jeremy Green, Dimitris Samaras, Prateek Prasanna:
Chest Radiograph Disentanglement for COVID-19 Outcome Prediction. MICCAI (7) 2021: 345-355 - [c20]Sudhir Suman, Gagandeep Singh, Nicole Sakla, Rishabh Gattu, Jeremy Green, Tej Phatak, Dimitris Samaras, Prateek Prasanna:
Attention Based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms. MICCAI (7) 2021: 356-366 - [c19]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Prateek Prasanna:
Attention-Based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. MICCAI (5) 2021: 824-833 - [c18]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Amit Gupta, Chao Chen, Joel H. Saltz, Prateek Prasanna:
Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. MIDL 2021: 384-398 - [i8]Ibrahim Hammoud, Prateek Prasanna, I. V. Ramakrishnan, Adam Singer, Mark Henry, Henry C. Thode:
EventScore: An Automated Real-time Early Warning Score for Clinical Events. CoRR abs/2102.05958 (2021) - [i7]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) - [i6]Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen:
TopoTxR: A Topological Biomarker for Predicting Treatment Response in Breast Cancer. CoRR abs/2105.06049 (2021) - [i5]Sudhir Suman, Gagandeep Singh, Nicole Sakla, Rishabh Gattu, Jeremy Green, Tej Phatak, Dimitris Samaras, Prateek Prasanna:
Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms. CoRR abs/2107.06276 (2021) - [i4]Aishik Konwer, Joseph Bae, Gagandeep Singh, Rishabh Gattu, Syed Ali, Jeremy Green, Tej Phatak, Prateek Prasanna:
Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. CoRR abs/2107.08330 (2021) - 2020
- [j2]Marwa Ismail, Virginia B. Hill, Volodymyr Statsevych, Evan Mason, Ramon Correa, Prateek Prasanna
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) - [c17]David Paredes, Prateek Prasanna
Automated Assessment of the Curliness of Collagen Fiber in Breast Cancer. ECCV Workshops (1) 2020: 267-279 - [c16]Amogh Hiremath, Rakesh Shiradkar, Nathaniel Braman, Prateek Prasanna
A combination of intra- and peri-tumoral deep features from prostate bi-parametric MRI can distinguish clinically significant and insignificant prostate cancer. Medical Imaging: Computer-Aided Diagnosis 2020 - [c15]Marwa Ismail, Ramon Correa, Kaustav Bera, Ruchika Verma
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. MICCAI (2) 2020: 305-314 - [c14]Ruiwen Ding, Prateek Prasanna, Germán Corredor, Cheng Lu
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores. Medical Imaging: Digital Pathology 2020: 1132003 - [i3]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) - [i2]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) - [i1]Joseph Bae, Saarthak Kapse, Gagandeep Singh, Tej Phatak, Jeremy Green, Nikhil Madan, Prateek Prasanna:
Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. CoRR abs/2007.08028 (2020)
2010 – 2019
- 2019
- [c13]Prateek Prasanna
Spatial arrangement of leakage patterns in diabetic macular edema is associated with tolerance of aflibercept treatment interval length: preliminary findings. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095311 - [c12]Prateek Prasanna
Morphology of vascular network in eyes with diabetic macular edema varies based on tolerance of aflibercept treatment interval length: preliminary findings. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 1095312 - [c11]Mohammadhadi Khorrami
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. Medical Imaging: Computer-Aided Diagnosis 2019: 109500R - [c10]Niha G. Beig, Prateek Prasanna
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 - [c9]Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Medical Imaging: Computer-Aided Diagnosis 2019: 109501E - 2018
- [c8]Cheng Lu
Feature Driven Local Cell Graph (FeDeG): Predicting Overall Survival in Early Stage Lung Cancer. MICCAI (2) 2018: 407-416 - [c7]Nathaniel Braman
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response. MICCAI (2) 2018: 803-811 - 2017
- [c6]Niha G. Beig
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Medical Imaging: Computer-Aided Diagnosis 2017: 101341U - [c5]Prateek Prasanna
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis. MICCAI (2) 2017: 459-467 - [c4]Jacob Antunes, Prateek Prasanna
RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. MICCAI (2) 2017: 468-476 - 2016
- [j1]Prateek Prasanna
Automated Crack Detection on Concrete Bridges. IEEE Trans Autom. Sci. Eng. 13(2): 591-599 (2016) - 2014
- [c3]Pallavi Tiwari, Prateek Prasanna
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI. Medical Imaging: Computer-Aided Diagnosis 2014: 90352B - [c2]Prateek Prasanna
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI. MICCAI (3) 2014: 73-80 - 2013
- [c1]Prateek Prasanna
Decision support system for detection of diabetic retinopathy using smartphones. PervasiveHealth 2013: 176-179
Coauthor Index
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