Arunava Chakravarty

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 23

Top Topics

Multiple Instance

Joint Segmentation

Top Venues

Comput. Methods Programs Biomed.

Publications

Dmitrii A. Lachinov, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Learning Spatio-Temporal Model of Disease Progression With NeuralODEs From Longitudinal Volumetric Data. IEEE Trans. Medical Imaging 43 (3) (2024)
Taha Emre, Arunava Chakravarty, Dmitrii A. Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Time-Equivariant Contrastive Learning for Degenerative Disease Progression in Retinal OCT. CoRR (2024)
Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT. CoRR (2023)
Taha Emre, Marzieh Oghbaie, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT: A PINNACLE Study Report. OMIA@MICCAI (2023)
Arunava Chakravarty, Taha Emre, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Morph-SSL: Self-Supervision with Longitudinal Morphing to Predict AMD Progression from OCT. CoRR (2023)
Taha Emre, Arunava Chakravarty, Antoine Rivail, Dmitrii A. Lachinov, Oliver Leingang, Sophie Riedl, Julia Mai, Hendrik P. N. Scholl, Sobha Sivaprasad, Daniel Rueckert, Andrew J. Lotery, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs. CoRR (2023)
Taha Emre, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
TINC: Temporally Informed Non-contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes. MICCAI (2) (2022)
Taha Emre, Arunava Chakravarty, Antoine Rivail, Sophie Riedl, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
TINC: Temporally Informed Non-Contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes. CoRR (2022)
Dmitrii A. Lachinov, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt-Erfurth, Hrvoje Bogunovic
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data. CoRR (2022)
Arunava Chakravarty, Avik Kar, Ramanathan Sethuraman, Debdoot Sheet
Federated Learning for Site Aware Chest Radiograph Screening. ISBI (2021)
Arunava Chakravarty, Tandra Sarkar, Nirmalya Ghosh, Ramanathan Sethuraman, Debdoot Sheet
Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening. CoRR (2020)
Arunava Chakravarty, Tandra Sarkar, Nirmalya Ghosh, Ramanathan Sethuraman, Debdoot Sheet
Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening. EMBC (2020)
Sarath Chandra K, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms. EMBC (2020)
Sarath Chandra K, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms. CoRR (2020)
Arka Mitra, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs. CoRR (2020)
Arka Mitra, Arunava Chakravarty, Nirmalya Ghosh, Tandra Sarkar, Ramanathan Sethuraman, Debdoot Sheet
A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs. EMBC (2020)
Arunava Chakravarty, Jayanthi Sivaswamy
RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation. IEEE J. Biomed. Health Informatics 23 (3) (2019)
Arunava Chakravarty, Divya Jyothi Gaddipati, Jayanthi Sivaswamy
Construction of a Retinal Atlas for Macular OCT Volumes. ICIAR (2018)
Arunava Chakravarty, Jayanthi Sivaswamy
A Deep Learning based Joint Segmentation and Classification Framework for Glaucoma Assesment in Retinal Color Fundus Images. CoRR (2018)
Arunava Chakravarty, Jayanthi Sivaswamy
A supervised joint multi-layer segmentation framework for retinal optical coherence tomography images using conditional random field. Comput. Methods Programs Biomed. 165 (2018)
Arunava Chakravarty, Jayanthi Sivaswamy
Joint optic disc and cup boundary extraction from monocular fundus images. Comput. Methods Programs Biomed. 147 (2017)
Arunava Chakravarty, Jayanthi Sivaswamy
End-to-End Learning of a Conditional Random Field for Intra-retinal Layer Segmentation in Optical Coherence Tomography. MIUA (2017)
Arunava Chakravarty, Jayanthi Sivaswamy
Glaucoma classification with a fusion of segmentation and image-based features. ISBI (2016)
Ujjwal, Arunava Chakravarty, Jayanthi Sivaswamy
An assistive annotation system for retinal images. ISBI (2015)
Arunava Chakravarty, Jayanthi Sivaswamy
Coupled Sparse Dictionary for Depth-Based Cup Segmentation from Single Color Fundus Image. MICCAI (1) (2014)
Ujjwal, K. Sai Deepak, Arunava Chakravarty, Jayanthi Sivaswamy
Visual saliency based bright lesion detection and discrimination in retinal images. ISBI (2013)
Mark J. J. P. van Grinsven, Arunava Chakravarty, Jayanthi Sivaswamy, Thomas Theelen, Bram van Ginneken, Clara I. Sánchez
A Bag of Words approach for discriminating between retinal images containing exudates or drusen. ISBI (2013)