NLM’s image processing focuses on data science research in biomedical image and signal processing, artificial intelligence, and machine learning to support automated clinical decision-making in disease screening and diagnostics. This area of research includes image and text analysis for clinical research, exploration of visual content relevant to disease in images and video, and visual information retrieval for embedding automated decision-support systems in diagnostic and treatment pathways.
Tenure Track Investigator, Computational Health Research Branch, LHNCBC
Sameer Antani, PhD
- Investigating the use of biomedical image and signal processing for clinical support
- Developing cervical cancer screening and diagnostics (in collaboration with the National Cancer Institute)
- Developing HIV+ and drug-resistant tuberculosis screening from chest X-rays (in collaboration with the National Institute of Allergy and Infectious Diseases (NIAID)
- Developing malaria screening from thin and thick smears (in collaboration with NIAID)
- Exploring craniofacial dysmorphism/malocclusion detection (in collaboration with the National Institute of Dental and Craniofacial Research)
Senior Investigator, Computational Biology Branch, NCBI
Zhiyong Lu, PhD
- Exploring the use of medical text/image analysis for autonomous disease diagnosis and prognosis
- Developing a novel, data-driven approach for automated age-related macular degeneration diagnosis and prognosis, called DeepSeeNet (in collaboration with the National Eye Institute)
- Developing automatic annotation of chest X-rays from radiology reports, using the NIH ChestX-ray8 dataset (in collaboration with the NIH Clinical Center)
