Department
Computer Science
Event Website
http://wmh.isi.uu.nl/
Start Date
8-11-2017 10:00 AM
End Date
8-11-2017 12:00 PM
Description
Small vessel disease plays a crucial role in stroke, dementia, and ageing. White matter hyperintensities (WMH) of vascular origin are one of the main consequences of small vessel disease and well visible on brain MR images. Quantification of WMH volume, location, and shape is of key importance in clinical research studies and likely to find its way into clinical practice; supporting diagnosis, prognosis, and monitoring of treatment for dementia and other neurodegenerative diseases. It has been noted that visual rating of WMH has important limitations and hence a more detailed segmentation of WMH is preferred. Various automated WMH segmentation techniques have been developed, to provide quantitative measurements and replace time-consuming, observer-dependent delineation procedures.
NLP LOGIX developed an automated algorithm for automatically segmenting white matter hyperintensities using an advanced modeling technique called deep learning.
Applied Deep Learning: Automated segmentation of White Matter Hyperintensities (WMH) on brain MR images
Small vessel disease plays a crucial role in stroke, dementia, and ageing. White matter hyperintensities (WMH) of vascular origin are one of the main consequences of small vessel disease and well visible on brain MR images. Quantification of WMH volume, location, and shape is of key importance in clinical research studies and likely to find its way into clinical practice; supporting diagnosis, prognosis, and monitoring of treatment for dementia and other neurodegenerative diseases. It has been noted that visual rating of WMH has important limitations and hence a more detailed segmentation of WMH is preferred. Various automated WMH segmentation techniques have been developed, to provide quantitative measurements and replace time-consuming, observer-dependent delineation procedures.
NLP LOGIX developed an automated algorithm for automatically segmenting white matter hyperintensities using an advanced modeling technique called deep learning.
https://digitalcommons.unf.edu/dhi/2017/Fall/8
Comments
Hello!
I am an adjunct teaching a database systems class this fall. My company (NLPLOGIX) develops algorithms for automating the reading of digital images - primarily in healthcare (MRI, CT, Pathology, etc ...). We often enter our algorithms into challenges - the attached paper is part of the write up we did for a recent challenge.
I am not sure if this type of project is what you are looking for, but I figured I would submit it anyway.
Matt.