11 citations · 11 across the 7 of their papers we have counts for
8 papers
GliomaINK: A Tumor and Anatomy Conditioned Flow Matching Framework for 3D MRI Sequence Synthesis in Glioma Patients
Moinak Bhattacharya, Annie Singh, Mohammad Chaudhry +2
Background: Incomplete multiparametric MR examinations limit glioma characterization and downstream AI tools. Generative models can synthesize missing MRI sequences, but anatomical…
SoC-DT: Standard-of-Care Aligned Digital Twins for Patient-Specific Tumor Dynamics
Moinak Bhattacharya, Gagandeep Singh, Prateek Prasanna
Accurate prediction of tumor trajectories under standard-of-care (SoC) therapies remains a major unmet need in oncology. This capability is essential for optimizing treatment plann…
Anatomy-DT: A Cross-Diffusion Digital Twin for Anatomical Evolution
Moinak Bhattacharya, Gagandeep Singh, Prateek Prasanna
Accurately modeling the spatiotemporal evolution of tumor morphology from baseline imaging is a pre-requisite for developing digital twin frameworks that can simulate disease progr…
NeuroRAD-FM: A Foundation Model for Neuro-Oncology with Distributionally Robust Training
Moinak Bhattacharya, Angelica P. Kurtz, Fabio M. Iwamoto +2
Neuro-oncology poses unique challenges for machine learning due to heterogeneous data and tumor complexity, limiting the ability of foundation models (FMs) to generalize across coh…
GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs
Moinak Bhattacharya, Gagandeep Singh, Shubham Jain +1
In this work, we present GazeLT, a human visual attention integration-disintegration approach for long-tailed disease classification. A radiologist's eye gaze has distinct patterns…
ImmunoDiff: A Diffusion Model for Immunotherapy Response Prediction in Lung Cancer
Moinak Bhattacharya, Judy Huang, Amna F. Sher +3
Accurately predicting immunotherapy response in Non-Small Cell Lung Cancer (NSCLC) remains a critical unmet need. Existing radiomics and deep learning-based predictive models rely…
TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs
Fan Wang, Zhilin Zou, Nicole Sakla +8
Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structure…
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models
Moinak Bhattacharya, Gagandeep Singh, Shubham Jain +1
In this work, we present RadGazeGen, a novel framework for integrating experts' eye gaze patterns and radiomic feature maps as controls to text-to-image diffusion models for high f…