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Alilou’s research focuses on applying computer vision and machine learning techniques for automatic analysis of chest CT scans. The resulting technology aids radiologists and pathologists with automatic detection, quantification, diagnosis, and treatment response prediction of lung cancer and other lung diseases. |
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Human musculoskeletal modeling and development of control systems for rehabilitation of individuals with spinal cord injury and other balance disorders. Design of rehabilitation devices for physically challenged individuals.
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Dr Janowczyk’s research focuses on applying machine learning and computer vision algorithms to digital pathology images. The resulting computational models aid pathologists in many common tasks, such as disease detection, grading, and the prediction of prognosis and therapy response. |
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Dr Lu’s research focuses on developing novel computational tools for identifying sub-visual image features from medical images and utilizing these features for disease classification, grading and prognosis in the context of breast cancer, head&neck cancer, and lung cancer.
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Building novel computational tools and machine learning models for characterization, diagnosis and prognosis of cancer on imaging.
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Development of a live-time imaging technique to rapidly and reliably identify basal and squamous skin cancer in the margins of conventionally resected skin cancer samples that would significantly impact the quality of patient care.
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Development of targeted imaging agents for detection and imaged-guided surgery of prostate cancer. Preclinical evaluation of PSMA-targeted theranostic agents for photodynamic therapy of prostate cancer.
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Nanotechnology for Cancer Diagnosis and Treatment; Imaging and Manipulation of Tumor Microenvironment; Cancer Immunotherapy; Adoptive T cell Immunotherapy |
