10 papers
Geodesic-informed Generative Diffusion Model For Topology-preserved Image Video Generation
Nian Wu, Nivetha Jayakumar, Jiarui Xing +1
Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, including but not limited to synthesis, reconstruction, and segmentatio…
CalcSeg: Confidence-aware 3D Latent Context Curriculum Learning For Myocardial Scar Segmentation From Single-Stack LGE-CMRs
Nivetha Jayakumar, Hannah Kim, Amit R. Patel +1
Myocardial scar segmentation from single-stack late gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) imaging has been a longstanding and clinically important challenge, par…
4DLoG: Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model
Nivetha Jayakumar, Swakshar Deb, Bahram Jafrasteh +2
Modeling and predicting neurodegenerative disease progression from medical images remains a major challenge in medical AI, with significant implications for early diagnosis, diseas…
Curriculum-Guided Myocardial Scar Segmentation for Ischemic and Non-ischemic Cardiomyopathy
Nivetha Jayakumar, Jonathan Pan, Shuo Wang +6
Identification and quantification of myocardial scar is important for diagnosis and prognosis of cardiovascular diseases. However, reliable scar segmentation from Late Gadolinium E…
IGG: Image Generation Informed by Geodesic Dynamics in Deformation Spaces
Nian Wu, Nivetha Jayakumar, Jiarui Xing +1
Generative models have recently gained increasing attention in image generation and editing tasks. However, they often lack a direct connection to object geometry, which is crucial…
TPIE: Topology-Preserved Image Editing With Text Instructions
Nivetha Jayakumar, Srivardhan Reddy Gadila, Tonmoy Hossain +2
Preserving topological structures is important in real-world applications, particularly in sensitive domains such as healthcare and medicine, where the correctness of human anatomy…
LaMoD: Latent Motion Diffusion Model For Myocardial Strain Generation
Jiarui Xing, Nivetha Jayakumar, Nian Wu +3
Motion and deformation analysis of cardiac magnetic resonance (CMR) imaging videos is crucial for assessing myocardial strain of patients with abnormal heart functions. Recent adva…
An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping
Rugved Chavan, Gabriel Hyman, Zoraiz Qureshi +10
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A…
SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction
Nivetha Jayakumar, Tonmoy Hossain, Miaomiao Zhang
3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achie…
Multimodal Deep Learning to Differentiate Tumor Recurrence from Treatment Effect in Human Glioblastoma
Tonmoy Hossain, Zoraiz Qureshi, Nivetha Jayakumar +5
Differentiating tumor progression (TP) from treatment-related necrosis (TN) is critical for clinical management decisions in glioblastoma (GBM). Dynamic FDG PET (dPET), an advance…