Tracking multiple neurons on worm images

Toufiq Parag; Victoria Butler; Dmitri Chklovskii

doi:10.1117/12.2000087

13 March 2013 Tracking multiple neurons on worm images

Toufiq Parag, Victoria Butler, Dmitri Chklovskii

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86692P (2013) https://doi.org/10.1117/12.2000087
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

We are interested in establishing the correspondence between neuron activity and body curvature during various movements of C. Elegans worms. Given long sequences of images, specifically recorded to glow when the neuron is active, it is required to track all identifiable neurons in each frame. The characteristics of the neuron data, e.g., the uninformative nature of neuron appearance and the sequential ordering of neurons, renders standard single and multi-object tracking methods either ineffective or unnecessary for our task. In this paper, we propose a multi-target tracking algorithm that correctly assigns each neuron to one of several candidate locations in the next frame preserving shape constraint. The results demonstrate how the proposed method can robustly track more neurons than several existing methods in long sequences of images.

Citation Download Citation

Toufiq Parag, Victoria Butler, and Dmitri Chklovskii "Tracking multiple neurons on worm images", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692P (13 March 2013); https://doi.org/10.1117/12.2000087

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