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Updated: Jan 27, 2026

Visualization of Endosome Dynamics in Living Nerve Terminals with Four-dimensional Fluorescence Imaging
Published on: April 16, 2014
Automatic Endosomal Structure Detection And Localization in Fluorescence Microscopic Images
Dongyun Lin1, Zhiping Lin1, Ramraj Velmurugan2
1School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore.
Abstract:
This paper proposes a modified spatially-constrained similarity measure (mSCSM) method for endosomal structure detection and localization under the bag-of-words (BoW) framework. To our best knowledge, the proposed mSCSM is the first method for fully automatic detection and localization of complex subcellular compartments like endosomes. Essentially, a new similarity score and a novel two-stage output control scheme are proposed for localization by extracting discriminative information within a group of query images. Compared with the original SCSM which is formulated for instance localization, the proposed mSCSM can address category based localization problems. The preliminary experimental results show the proposed mSCSM can correctly detect and localize 79.17% of the existing endosomal structures in the microscopic images of human myeloid endothelial cells.
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