1 citations · 1 across the 8 of their papers we have counts for
8 papers
Self-Supervised Cardiac Phase Detection via Single-Parameter Latent Orbits
John Bonnici, Matthew Baugh, Aleksandra Kulbaka +3
Accurate identification of end-diastole (ED) and end-systole (ES) in echocardiography underpins the quantification of ventricular function, yet manual selection of these key frames…
Image Generation Diversity Issues and How to Tame Them
Mischa Dombrowski, Weitong Zhang, Sarah Cechnicka +2
Generative methods now produce outputs nearly indistinguishable from real data but often fail to fully capture the data distribution. Unlike quality issues, diversity limitations i…
JVID: Joint Video-Image Diffusion for Visual-Quality and Temporal-Consistency in Video Generation
Hadrien Reynaud, Matthew Baugh, Mischa Dombrowski +3
We introduce the Joint Video-Image Diffusion model (JVID), a novel approach to generating high-quality and temporally coherent videos. We achieve this by integrating two diffusion…
Data-Efficient Generation for Dataset Distillation
Zhe Li, Weitong Zhang, Sarah Cechnicka +1
While deep learning techniques have proven successful in image-related tasks, the exponentially increased data storage and computation costs become a significant challenge. Dataset…
URCDM: Ultra-Resolution Image Synthesis in Histopathology
Sarah Cechnicka, James Ball, Matthew Baugh +6
Diagnosing medical conditions from histopathology data requires a thorough analysis across the various resolutions of Whole Slide Images (WSI). However, existing generative methods…
Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics
Weitong Zhang, Chengqi Zang, Liu Li +3
Inverse problems describe the process of estimating the causal factors from a set of measurements or data. Mapping of often incomplete or degraded data to parameters is ill-posed,…
Ultra-Resolution Cascaded Diffusion Model for Gigapixel Image Synthesis in Histopathology
Sarah Cechnicka, Hadrien Reynaud, James Ball +5
Diagnoses from histopathology images rely on information from both high and low resolutions of Whole Slide Images. Ultra-Resolution Cascaded Diffusion Models (URCDMs) allow for the…
Realistic Data Enrichment for Robust Image Segmentation in Histopathology
Sarah Cechnicka, James Ball, Hadrien Reynaud +3
Poor performance of quantitative analysis in histopathological Whole Slide Images (WSI) has been a significant obstacle in clinical practice. Annotating large-scale WSIs manually i…