141 citations · 198 across the 3 of their papers we have counts for
3 papers
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset
Kelly Payette, Priscille de Dumast, Hamza Kebiri +17
It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders.…
Exploring Brain-wide Development of Inhibition through Deep Learning
Asim Iqbal, Asfandyar Sheikh, Theofanis Karayannis
We introduce here a fully automated convolutional neural network-based method for brain image processing to Detect Neurons in different brain Regions during Development (DeNeRD). O…
Developing Brain Atlas through Deep Learning
Asim Iqbal, Romesa Khan, Theofanis Karayannis
Neuroscientists have devoted significant effort into the creation of standard brain reference atlases for high-throughput registration of anatomical regions of interest. However, v…