TOM 21.02.2018

Venue: Viikki Infocenter room 139, live stream in Meilahti Terkko auditorium 2013

Timing: 16:00 onwards

Presenter: Ilida Suleymanova

A deep convolutional neural network approach for astrocyte detection

Astrocytes are involved in brain pathologies such as trauma or stroke, neurodegenerative disorders like Alzheimer’s and Parkinson’s, and many others. Determining the timing of morphological and biochemical changes is important for understanding the discrete steps of cells function in health and diseases. Most widely used approaches for image-processing and quantification analysis are either manual cell counting or semi-automatic techniques. Currently, we lack a fully-automated and efficient image analysis tool to quantify astrocytes. In this study, we developed a fast and fully automated a graphical software that assesses the number of astrocytes based on Deep Convolutional Neural Networks (DCNN) technique. Based on the fast-learnable image features of this type of cells, DCNN may grant the most efficient solution. The proposed method shows strong positive correlation with the manual counts.


For those who are unable to go to Viikki, we have booked Terkko auditorium 2013 in Meilahti, where you can follow live stream of this month’s TOM session