The 3D and Quantitative Imaging Laboratory was developed in 1996 at Stanford University School of Medicine by directors Geoffrey Rubin, MD, and Sandy Napel, PhD, with the mission of developing and applying innovative techniques for efficient analysis and display of medical imaging data through interdisciplinary collaboration. FEATURED PUBLICATIONS 1. ... Clinical Assistant Professor of Medicine in Gastroenterology and Hepatology at Stanford University (Palo Alto, California) Vani Konda, M.D. Support Lucile Packard Children's Hospital Stanford and child and maternal health. A recent focus of the lab is in deep learning methods for automated image classification, lesion detetction, segmentation, and clinical prediction. Dr. Rubin founded Stanford's 3D Imaging laboratory serving as its Medical Director and led the section of Cardiovascular Imaging. Eun-Ju Chang, Ph.D. Current Position: Assistant Professor, Department of Anatomy & Cell Biology, University of Ulsan College of Medicine, Seoul, Korea Contact: cej1103@yahoo.com Tina Rodriguez. Our research group uses artificial intelligence (AI) and computational methods to leverage the information in radiology images to enable biomedical discovery and to guide physicians in personalized care. V. Akondi and A. Dubra, Opt. SLAC National Accelerator Laboratory - Rubin Observatory Camera Assembly TimeLapse Just as biology has been revolutionized by online genetic data, our goal is to advance radiology by making the content in images and medical texts computable and to electronically correlate images and texts with other clinical data such as pathology and molecular data. The grant entitled “Distributed computation of predictive models for precision medicine in cancer” will focus on developing methods and tools for training AI models relevant to cancer through federated computational methods that do not require any data sharing and that will propel multi-institutional collaborations for creating more robust AI models. Our ultimate goal is to bridge the divide between radiological knowledge and practice--for all radiological knowledge and research data to be structured, accessed, and processed by computers so that we can create and deploy decision support applications in image workstations to improve radiologist clinical effectiveness. The site facilitates research and collaboration in academic endeavors. Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative (18)F FDG-PET/CT metrics. We are engaged in scientific collaborations with the National Center for Biomedical Ontology, and we participate in a national working group that is developing imaging informatics infrastructure for the cancer Biomedical Informatics Grid program at National Cancer Institute. Tom Rubin is Special Counsel at Quinn Emanuel Urquhart & Sullivan and Lecturer in Law at Stanford Law School, where he is teaching a seminar entitled Lawyering for Innovation in the fall of 2017. Lab Research Coordinator. Laboratory of Quantitative Imaging and Artificial Intelligence (QIAI) Daniel L. Rubin, MD, MS Professor of Biomedical Data Science, Radiology, and Medicine (Biomedical Informatics) The site facilitates research and collaboration in academic endeavors. Average gradient of Zernike polynomials over polygons. The Rubin Lab also serves as the Center for Imaging Informatics at Stanford University Hospital. We are developing novel methods to tackle recent challenges in AI related to limited quality labeled data, including weak learning, multi-task learning, and multi-modal models. Bio: Daniel L. Rubin, MD, MS is Professor of Biomedical Data Science, Radiology, Medicine (Biomedical Informatics), and Ophthalmology (courtesy) at Stanford University. Our work develops and translates basic biomedical informatics methods to improve radiology practice and decision making in several areas to enable precision healthcare. On May 10, 2017, Dr. Assaf Hoogi, a Postdoctoral Scholar in the Dr. Rubin's laboratory received the prestigeous Larry Clarke QIN Young Investigator Travel Award for is outstanding and innovative work in adaptive methods for image segmentation and career vision for advancing quantitative imaging. Express 28, 18876-18886 (2020) The Rubin Lab also serves as the Center for Imaging Informatics at Stanford University Hospital. The objectives of her laboratory research are to identify specific inflammatory pathways that may be targeted to prevent and treat neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. Stanford Institutes of Medical Research Program, Stanford University School of Medicine, Stanford, California 94305 ... 530 Tam, Barker, and Rubin: Pathology image normalization for improved feature extraction 530 F . Consequently, radiologists and clini- ... * Daniel L. Rubin dlrubin@stanford.edu Selen Bozkurt selenb@stanford.edu Emel Alkim ealkim@stanford.edu Imon … Thanks to its plug-in architecture, ePAD can be used to support a wide range of imaging-based projects. We are pleased to announce that ePAD project (http://epad.stanford.edu) of the QIAI Lab, "ePAD: A platform to enable machine learning and AI application development in medical imaging" (B-0906) has been selected to receive the Best Scientific Paper Presentation Award at the 2019 European Congress of Radiology in Imaging Informatics, https://www.myesr.org/congress, Medical School Office Building (MSOB) He is Principal Investigator of two centers in the National Cancer Institute's Quantitative Imaging Network (QIN) and is Director of Biomedical Informatics for the Stanford Cancer Institute. ... Daniel Rubin. He is Principal Investigator of two centers in the National Cancer Institute's Quantitative Imaging Network (QIN) and is Director of Biomedical Informatics for the Stanford Cancer Institute. Stanford Rubin’s practice centers on estate and tax planning and trust and probate administration matters for individuals of substantial net worth. Yoni Samuel Rubin, PhD is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). We are developing novel methods to tackle recent challenges in AI related to limited quality labeled data, including weak learning, multi-task learning, and multi-modal models. The case describes what Rubin did to transform the culture and operations of Stanford Health Care and, specifically, what he did to build support among the various constituencies so critical to his being successful: the medical school physicians, the board of the hospital, and the colleagues already at Stanford. Phone: (650) 497-0945 | Fax: (650) 497-1990, Phone: (650) 723-9529 | Fax: (650) 723-5795, Laboratory of Quantitative Imaging and Artificial Intelligence (QIAI), Stanford Center for Biomedical Informatics Research. The Rubin Lab is in the Department of Biomedical Data Science and the Department of Radiology in the Stanford University School of Medicine, and is a core faculty laboratory in the Biomedical Informatics Training Program at Stanford University. SLAC National Accelerator Laboratory - Vera C. Rubin Observatory LSST Camera The DOE-funded effort to build the Rubin Observatory LSST Camera (LSSTCam) is managed by SLAC National Accelerator Laboratory (SLAC). We also develop tools to efficiently and thoroughly capture the semantic terms radiologists use to describe lesions; standardized terminologies to enable radiologists to describe lesions comprehensively and consistently; image processing methods to characterize lesions; content-based image retrieval with structured image information to enable radiologists to find similar images; methods to enable physicians to quantitatively and reproducibly assess tumor burden in images and to more effectively monitor treatment response in cancer treatment; natural language techniques to enable uniform indexing, searching, and retrieval of radiology information resources such as radiology reports; and decision support applications that relate radiology findings to diagnoses to improve diagnostic accuracy. Protocol for production of the three datasets; heA, heB, and ihcB. Jorie Singer. A freely available quantitative imaging informatics platform, developed by the Rubin Lab at Stanford Medicine Radiology at Stanford University. and Daniel L. Rubin2,4 1 School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China 2 Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA The grant is entitled “Integrating omics and quantitative imaging data in co-clinical trials to predict treatment response in triple negative breast cancer.” The ePAD technology (http://epad.stanford.edu) developed by the QIAI Lab is central to this grant by bringing quantitative image analysis methods to small animal imaging and unifying quantitative assessment of cancer on images in both animal and human studies to catalyze research in the co-clinical trials paradigm. 1. Clinical Research Coordinator. Dr. Rubin's Lab Homepage Just as biology has been revolutionized by online genetic data, now clinical medicine can be transformed by mining huge image repositories and electronically correlating image data with pathology and molecular data. The ePAD technology (http://epad.stanford.edu) that the Rubin lab has been developing is central to this grant, bringing quantitative image analysis methods to small animal imaging and unifying quantitative assessment of cancer on images in both animal and human studies to catalyze research in the co-clinical trials paradigm. We are pleased to announce that the QIAI Lab has been awarded a second grant from the NIH, a U01 under NCI’s Informatics Technologies for Cancer Research and Management (ITCR) program. Yoni Samuel Rubin, PhD is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). ... Clinical Assistant Professor of Medicine in Gastroenterology and Hepatology at Stanford University (Palo Alto, California) Vani Konda, M.D. Lee Rubin, Ph.D. Our laboratory is broadly interested in the mechanisms underlying changes in the nervous system as a result of aging or disease, as well as the interactions between the nervous system and the rest of the body that mediate health versus disease. ... Stanford … For many years he served as Chief Intellectual Property Strategy Counsel and the head of the copyright, trademark and trade secret group at Microsoft. ... Daniel Rubin. We collaborate with a variety of investigators at Stanford both in Radiology and Oncology as well as with investigators outside Stanford. Stanford Medicine Habtezion Lab ... a Gastroenterology Fellowship at the University of Toronto, and a post doctoral research fellowship at Stanford University. Dr. Rubin founded Stanford's 3D Imaging laboratory serving as its Medical Director and led the section of Cardiovascular Imaging. Just as biology has been revolutionized by online genetic data, our goal is to advance radiology by making the content in images and medical texts computable and to electronically correlate images and texts with other clinical data such as pathology and molecular data. SLAC National Accelerator Laboratory is a U.S. Department of Energy (DOE) Office of Science laboratory operated by Stanford University. Abigail Zuckerman. We are please to announce that the QIAI Lab is part of a team that was awarded a U24 grant under NCI’s Oncology Co-Clinical Imaging Research Resources to Encourage Consensus on Quantitative Imaging Methods and Precision Medicine, which is a new network of sites developing innovative methods to enable co-clinical (animal/human) trials. The NSF-funded LSST (now Rubin Observatory) Project Office for construction was established as an operating center under management of the Association of Universities for Research in Astronomy (AURA). Rubin Observatory is a federal project jointly funded by the National Science Foundation and the Department of Energy, with early construction funding received from private donations through the LSST Corporation. Our research group uses artificial intelligence (AI) and computational methods to leverage the information in radiology images to enable biomedical discovery and to guide physicians in personalized care. ... Amanda Rubin, JD, PhD Cooley LLP, Palo Alto, CA. STARR Cohort Discovery The 3D and Quantitative Imaging Laboratory was developed in 1996 at Stanford University School of Medicine by directors Geoffrey Rubin, MD, and Sandy Napel, PhD, with the mission of developing and applying innovative techniques for efficient analysis and display of medical imaging data through interdisciplinary collaboration. Lab Research Coordinator. Circular ecDNA promotes accessible chromatin and high oncogene expression. Clinical Research Coordinator. Greater Boston Area Partner, Hemenway & Barnes LLP Law Practice Education Boston University School of Law 1987 — 1991 JD University of Wisconsin-Madison 1976 — 1980 BS, Nursing Experience Hemenway & Barnes LLP September 2001 - Present Hill & Barlow 1991 - 2001 Bristol-Myers Squibb 1984 - 1988 Stanford University Medical Center 1980 - 1984 The Rubin Lab is in the Department of Biomedical Data Science and the Department of Radiology in the Stanford University School of Medicine, and is a core faculty laboratory in the Biomedical Informatics Training Program at Stanford University. SLAC National Accelerator Laboratory is a U.S. Department of Energy (DOE) Office of Science laboratory operated by Stanford University. JB, Plevritis SK, Rubin DL, Leung AN, Napel S, Quon A. Kun-Hsing Yu1,2, Ce Zhang3, Gerald J. Berry4, Russ B. Altman1, Christopher Re´3, Daniel L. Rubin1,* & Michael Snyder2,* Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is indispensable for its diagnosis. Rubin Observatory is a federal project jointly funded by the National Science Foundation and the Department of Energy, with early construction funding received from private donations through the LSST Corporation. We also develop tools to efficiently and thoroughly capture the semantic terms radiologists use to describe lesions; standardized terminologies to enable radiologists to describe lesions comprehensively and consistently; image processing methods to characterize lesions; content-based image retrieval with structured image information to enable radiologists to find similar images; methods to enable physicians to quantitatively and reproducibly assess tumor burden in images and to more effectively monitor treatment response in cancer treatment; natural language techniques to enable uniform indexing, searching, and retrieval of radiology information resources such as radiology reports; and decision support applications that relate radiology findings to diagnoses to improve diagnostic accuracy. ePAD is a freely available quantitative imaging informatics platform, developed by the Rubin Lab at Stanford Medicine Radiology at Stanford University.Thanks to its plug-in architecture, ePAD can be used to support a wide range of imaging-based projects. 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