Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Sami S Brandt

Showing results (1-10 of 9) with videos related to

Pageof 1
Sort By:
IEEE Transactions on Bio-Medical Engineering|March 5, 2010
A Bayesian reconstruction method with marginalized uncertainty model for camera motion in microrotation imagingDanai Laksameethanasan, Sami S Brandt
IEEE Transactions on Pattern Analysis and Machine Intelligence|August 5, 2006
A generic camera model and calibration method for conventional, wide-angle, and fish-eye lensesJuho Kannala, Sami S Brandt
Physics in Medicine and Biology|April 30, 2014
Breast tissue segmentation from x-ray radiographsChen Chen, Mads Nielsen, Nico Karssemeijer, et al.
IEEE Transactions on Medical Imaging|May 26, 2011
An anatomically oriented breast coordinate system for mammogram analysisSami S Brandt, Gopal Karemore, Nico Karssemeijer, et al.
Physics in Medicine and Biology|October 21, 2014
A method to determine the mammographic regions that show early changes due to the development of breast cancerGopal Karemore, Mads Nielsen, Nico Karssemeijer, et al.
Microscopy Research and Technique|November 30, 2007
A Bayesian reconstruction method for micro-rotation imaging in light microscopyDanai Laksameethanasan, Sami S Brandt, Peter Engelhardt, et al.
IEEE Transactions on Medical Imaging|November 10, 2011
A Bayesian framework for automated cardiovascular risk scoring on standard lumbar radiographsKersten Petersen, Melanie Ganz, Peter Mysling, et al.
Medical Image Analysis|August 1, 2014
Segmentation of B-mode cardiac ultrasound data by Bayesian Probability MapsMattias Hansson, Sami S Brandt, Johan Lindström, et al.
Nordic Journal of Psychiatry|March 30, 2026
Don't predict if you cannot interpret: investigating the clinical viability of facial movements for machine-learning assisted diagnostics of bipolar disorderMartin Lund Trinhammer, Stella Graßhof, Lars Vedel Kessing, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Bio-Medical Engineering|March 5, 2010
A Bayesian reconstruction method with marginalized uncertainty model for camera motion in microrotation imagingDanai Laksameethanasan, Sami S Brandt
IEEE Transactions on Pattern Analysis and Machine Intelligence|August 5, 2006
A generic camera model and calibration method for conventional, wide-angle, and fish-eye lensesJuho Kannala, Sami S Brandt
Physics in Medicine and Biology|April 30, 2014
Breast tissue segmentation from x-ray radiographsChen Chen, Mads Nielsen, Nico Karssemeijer, et al.
IEEE Transactions on Medical Imaging|May 26, 2011
An anatomically oriented breast coordinate system for mammogram analysisSami S Brandt, Gopal Karemore, Nico Karssemeijer, et al.
Physics in Medicine and Biology|October 21, 2014
A method to determine the mammographic regions that show early changes due to the development of breast cancerGopal Karemore, Mads Nielsen, Nico Karssemeijer, et al.
Microscopy Research and Technique|November 30, 2007
A Bayesian reconstruction method for micro-rotation imaging in light microscopyDanai Laksameethanasan, Sami S Brandt, Peter Engelhardt, et al.
IEEE Transactions on Medical Imaging|November 10, 2011
A Bayesian framework for automated cardiovascular risk scoring on standard lumbar radiographsKersten Petersen, Melanie Ganz, Peter Mysling, et al.
Medical Image Analysis|August 1, 2014
Segmentation of B-mode cardiac ultrasound data by Bayesian Probability MapsMattias Hansson, Sami S Brandt, Johan Lindström, et al.
Nordic Journal of Psychiatry|March 30, 2026
Don't predict if you cannot interpret: investigating the clinical viability of facial movements for machine-learning assisted diagnostics of bipolar disorderMartin Lund Trinhammer, Stella Graßhof, Lars Vedel Kessing, et al.
Pageof 1