Three-Dimensional Shape Estimation of BHK Cell Clusters from a Still Image Based on Shape from Shading for In-SITU Microscopy

In this contribution, the Lee and Rosenfeld's local shape from shading (SFS) algorithm, the Tsai and Shah's linear SFS algorithm and the Bichsel and Pentland's propagation SFS algorithm are investigated with the aim of selecting the most suitable for three-dimensional shape estimation of clusters of mammalian baby hamster kidney cells (BHK cells) from an intensity image captured by an in-situ microscope in an industrial mammalian cell culture process. All three were implemented and tested using several thousand intensity images captured under varying experimental conditions. The Bichsel and Pentland's SFS algorithm was finally selected as the most suitable algorithm for three-dimensional shape estimation of BHK cell clusters. It is fast and provides less noise and more detailed depth estimates and therefore the best overall performance