Classification of red blood cell shapes in flow using outlier tolerant machine learning
Fig 7
Image montage of all false negative (left) and false positive (right) classified slippers with respect to manually obtained classification.
All cells being classified as croissants manually but not by the CNN (false negative slippers) are depicted in the left image, whereas all false positive slippers are shown in the right montage (cells classified as slipper shapes by automated analysis but not by hand). Additionally, each cell image contains a yellow box with the according CNN output values.