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Found 8 papers, 1 papers with code
Neural Ordinary Differential Equation based Sequential Image Registration for Dynamic Characterization
Leveraging Neural Ordinary Differential Equations (ODE) for registration, this extension work discusses how this framework can aid in the characterization of sequential biological processes.
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration
We demonstrate compelling improvements on image registration across a spectrum of modalities and anatomies by measuring structural and landmark overlap of the registered image volumes.
A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data
Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification.
Generative Adversarial Bayesian Optimization for Surrogate Objectives
To address this limitation, we propose generative adversarial Bayesian optimization (GABO) using adaptive source critic regularization, a task-agnostic framework for Bayesian optimization that employs a Lipschitz-bounded source critic model to constrain the optimization trajectory to regions where the surrogate function is reliable.
Towards Establishing Dense Correspondence on Multiview Coronary Angiography: From Point-to-Point to Curve-to-Curve Query Matching
Coronary angiography is the gold standard imaging technique for studying and diagnosing coronary artery disease.
The Role of Chain-of-Thought in Complex Vision-Language Reasoning Task
The study explores the effectiveness of the Chain-of-Thought approach, known for its proficiency in language tasks by breaking them down into sub-tasks and intermediate steps, in improving vision-language tasks that demand sophisticated perception and reasoning.
Ranked #1 on
Visual Reasoning
on Winoground
NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration
Deformable image registration (DIR), aiming to find spatial correspondence between images, is one of the most critical problems in the domain of medical image analysis.
Nested Scale Editing for Conditional Image Synthesis
We propose an image synthesis approach that provides stratified navigation in the latent code space.
