Medical Imaging Computing: From Data to Understanding
The development of new technologies that acquire large amounts of complex data is accelerating throughout medicine. Corresponding breakthroughs in accessible computation and algorithm development have made image analysis an indispensable tool for medical research and clinical practice. For example, image analysis enables the data acquired using diffusion tensor imaging (DTI) and functional magnetic resonance (fMRI) to reveal subject-specific structure and function of the brain.
The emerging field of medical image computing requires strong, interdisciplinary teams of researchers, physicians, and engineers. Building such teams is a challenge but ultimately rewarding process. The Surgical Planning Lab at Brigham and Women's Hospital was founded in 1990 to enable research in image computation within the hospital context. Today, the SPL is the hub of the National Alliance for Medical Image Computing, a national effort with international impact across biomedicine and, increasingly, other fields of science. NAMIC drives scientific and engineering innovation through interdisciplinary collaboration, application-driven development, a well-designed hardware and software infrastructure, and an open-source approach to dissemination and community building.
This presentation will describe how research ideas evolve into useful medical and scientific tools within the SPL and NAMIC environments.
Видео Medical Imaging Computing: From Data to Understanding канала Harvard University
The emerging field of medical image computing requires strong, interdisciplinary teams of researchers, physicians, and engineers. Building such teams is a challenge but ultimately rewarding process. The Surgical Planning Lab at Brigham and Women's Hospital was founded in 1990 to enable research in image computation within the hospital context. Today, the SPL is the hub of the National Alliance for Medical Image Computing, a national effort with international impact across biomedicine and, increasingly, other fields of science. NAMIC drives scientific and engineering innovation through interdisciplinary collaboration, application-driven development, a well-designed hardware and software infrastructure, and an open-source approach to dissemination and community building.
This presentation will describe how research ideas evolve into useful medical and scientific tools within the SPL and NAMIC environments.
Видео Medical Imaging Computing: From Data to Understanding канала Harvard University
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Deep Learning in Medical Imaging - Ben Glocker, Imperial College LondonMary Lou Jepsen: Breaking the Logjam in Medical ImagingImaging InformaticsUlugbek Kamilov: "Computational Imaging: Reconciling Models and Learning"Elizabeth Sweeney - Neuroimaging Analysis in RIntroduction to Radiology: Conventional RadiographyWhat’s the Difference Between an MRI and a CT?Artificial Intelligence Can Change the future of Medical Diagnosis | Shinjini Kundu | TEDxPittsburghBut what is a Neural Network? | Deep learning, chapter 1Introducing MRI: K-space: Features and Tricks (24 of 56)The Big Questions of Biomedical Engineering | Sofia Mehmood | TEDxYouth@PWHSTexture in Medical ImagesJohns Hopkins Medicine Virtual Tour for Prospective ApplicantsElectrical Engineering Vs Computer Engineering - How to Pick the Right MajorWhat Is Image Processing? – Vision CampusFourier transforms in image processing (Maths Relevance)Fourier Transform, Fourier Series, and frequency spectrumTaking hard lefts and the medical machine learning landscape with Zack Chase Lipton3rd Biomedical Image Analysis Summer School. Lecture of Ben Glocker, Medical Image Computing94 - Denoising MRI images (also CT & microscopy images)