46 citations
- Imperial College LondonGB9 papers
- University of OxfordGB3 papers
- British Heart FoundationGB2 papers
- National Heart Centre SingaporeSG2 papers
- Shanghai Medical College of Fudan UniversityCN2 papers
- University of BirminghamGB2 papers
- Arizona State UniversityUS1 paper
- Barts Health NHS TrustGB1 paper
- Birmingham Children's HospitalGB1 paper
- Birmingham Women’s and Children’s NHS Foundation TrustGB1 paper
- Center for NanoScienceDE1 paper
- Centre for Human GeneticsGB1 paper
10 papers
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics
Mengyun Qiao, Kathryn A McGurk, Shuo Wang +3
Understanding the structure and motion of the heart is crucial for diagnosing and managing cardiovascular diseases, the leading cause of global death. There is wide variation in ca…
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis
Jian-Qing Zheng, Yuanhan Mo, Yang Sun +5
In medical imaging, the diffusion models have shown great potential for synthetic image generation tasks. However, these approaches often lack the interpretable connections between…
A new twist on PIFE: photoisomerisation-related fluorescence enhancement
Evelyn Ploetz, Benjamin Ambrose, Anders Barth +12
PIFE was first used as an acronym for protein-induced fluorescence enhancement, which refers to the increase in fluorescence observed upon the interaction of a fluorophore, such as…
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy
Mengyun Qiao, Shuo Wang, Huaqi Qiu +4
Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical facto…
Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets
Sreejita Ghosh, Elizabeth S. Baranowski, Michael Biehl +3
Application of interpretable machine learning techniques on medical datasets facilitate early and fast diagnoses, along with getting deeper insight into the data. Furthermore, the…
Correspondence on ACMG STATEMENT: ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG) by Miller et al
Kathryn A. McGurk, Sean L. Zheng, Albert Henry +8
We were interested to read the recent update on recommendations for reporting of secondary findings in clinical sequencing1, and the accompanying updated list of genes in which sec…