Table of Contents

June 2018

We investigate the shape transitions of red blood cells flowing in micro-capillaries. A convolutional neural network (CNN) transforms bright-field images of cells into a set of abstract representations. The illustration shows different shape features of the same cell highlighted by the color scheme and dependent on the applied convolution kernel. Our approach allows for a quantitative classification of each recorded cell. According to the prevailing flow conditions, the CNN reveals the formation of two stable shapes, "slippers" and "croissants". Finally, a phase diagram assessed within a range of physiolocial relevant shear rates expresses the shape transition in between these states. Kihm et al.

Image Credit: Stephan Quint

Messages from ISCB

2018 ISCB Innovator Award recognizes M. Madan Babu

Christiana N. Fogg, Diane E. Kovats, Ron Shamir

2018 ISCB Overton Prize awarded to Cole Trapnell

Christiana N. Fogg, Diane E. Kovats, Ron Shamir


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Vivek Navale, Philip E. Bourne

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