65.5
Ahmad Golaraei
University of Toronto
Ahmad Golaraei has made significant contributions to the field of biomedical imaging and diagnostics through their research on wide-field multicontrast nonlinear microscopy for histopathology. Their work has expanded the capabilities of second-harmonic generation (SHG) microscopy, a technique that enables the non-invasive analysis of tissue structure and composition. By developing machine learning algorithms and exploring polarimetric SHG microscopy, Golaraei's research aims to improve cancer diagnostics, particularly in the detection of lung tumors, by providing detailed information on tumor margins and collagen fibril organization. These advancements hold great promise for the development of more accurate and non-invasive diagnostic tools for various diseases.