Le Lu
About Le Lu
Mission: redefining, architecting and positively improving health through intelligence human-in-the-loop computing! 1) Empowering physicians worldwide through close & seamless collaborations, 2) Making great things from impossible but imaginable to scientifically-viable and technically deliverable, 3) progressing novel clinician-lead, technology-driven effective workflows with clinical partners and humble but confident spirits. "Be the change to drive Clinical Healthcare Intelligence on Imaging and Informatics to impact patient care positively” Learned CAD 1.0; built CAD 2.0; re-building CAD 3.0; exploiting CAD 4.0 (CAD: image-text driven computer-aided diagnosis and patient/population risk profiling in unconstrained large-scale setting) Making unconstrained or much less constrained large scale computer-aided early detection and prevention of cancers and other pathologies, via hospital scale text/image/meta-data deep parsing. Precision medicine is the key, Precision medicine is now! In my previous NIH function, I conduct research activities on the cutting edge new methods and learning systems on 1), Deep parsing of large-scale clinical radiology image analytics and informatics (~1M patient cases at a hospital scale); 2), Imaging based computer-aided early cancer/pathology detection and clinical decision support systems (e.g., detecting and characterizing enlarged lymph node, abdominal imaging, colonic polyps, lung nodules, ILD, bone lesion and shape analysis). I am fortunate enough mentoring quite many Postdoc or IRTA fellows and helping them grow to shining stars! When at Siemens, I made significant technical contributions/innovations, responsible for all major Siemens Colon, Lung CAD product updates/releases (2006-2013). I lead the efforts on semantic vessel parsing and contributed several patents/papers for bone imaging. Specialties: Deep Learning for scalable Medical Imaging and Health Informatics, Generalizable, explainable, transferable Deep Learning