690 citations
- University of CambridgeGB17 papers
- Cancer Research UK Cambridge CenterGB9 papers
- Harvard UniversityUS4 papers
- University College LondonGB4 papers
- German Cancer Research CenterDE3 papers
- Heidelberg UniversityDE3 papers
- Institute of Cancer ResearchGB3 papers
- University Hospital HeidelbergDE3 papers
- Brigham and Women's HospitalUS2 papers
- European Bioinformatics InstituteGB2 papers
- Nokia (United Kingdom)GB2 papers
- University of LisbonPT2 papers
26 papers
Data-driven registration and modeling of brain deformation for image-guided neurosurgery
Tiago Assis, Colin P. Galvin, Joshua P. Castillo +12
Accurate compensation of brain deformation is critical for reliable image-guided neurosurgery. Surgical manipulation and tumor resection induce tissue motion, causing preoperative…
Leveraging large language models for structured information extraction from pathology reports
Jeya Balaji Balasubramanian, Daniel Adams, Ioannis Roxanis +4
Background: Structured information extraction from unstructured histopathology reports facilitates data accessibility for clinical research. Manual extraction by experts is time-co…
Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Healthcare System Administration using Deep Reinforcement Learning
Adi Shuchami, Teddy Lazebnik
Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding t…
A study of why we need to reassess full reference image quality assessment with medical images
Anna Breger, Ander Biguri, Malena Sabaté Landman +11
Image quality assessment (IQA) is indispensable in clinical practice to ensure high standards, as well as in the development stage of machine learning algorithms that operate on me…
Cancer-inspired Genomics Mapper Model for the Generation of Synthetic DNA Sequences with Desired Genomics Signatures
Teddy Lazebnik, Liron Simon-Keren
Genome data are crucial in modern medicine, offering significant potential for diagnosis and treatment. Thanks to technological advancements, many millions of healthy and diseased…
Unsupervised Domain Transfer with Conditional Invertible Neural Networks
Kris K. Dreher, Leonardo Ayala, Melanie Schellenberg +11
Synthetic medical image generation has evolved as a key technique for neural network training and validation. A core challenge, however, remains in the domain gap between simulatio…