Evaluating Techniques for Neuron Identification in Complex Cultures: A Deep Learning Approach
- Puerta, Paula
- Ozturk, Berke
- González, Víctor M.
- Villar, José R.
- Serrano Pertierra, Esther
- Joaquín Roca González (coord.)
- Dolores Ojados González (coord.)
- Juan Suardíaz Muro (coord.)
Editorial: Universidad Politécnica de Cartagena
ISBN: 978-84-17853-76-1
Año de publicación: 2023
Páginas: 464-467
Congreso: Congreso Anual de la Sociedad Española de Ingeniería Biomédica. CASEIB (41. 2023. Cartagena)
Tipo: Aportación congreso
Resumen
Microscopy image analysis of neurons cultures represents a formidable challenge due to their complex structure because of the dynamic nature of neurite tissue development, the neuron movement, the morphological changes, and the pres- ence of many elements in the cultures apart from neurons such as glial cells, dead cells, vesicles, etc. A rigorous eval- uation of deep learning techniques to address this intricate problem is undertaken in this study. Several methodolo- gies, including Instance Segmentation and Object Detection models, are scrutinized within a comprehensive experimen- tal framework. The efficacy of the Instance Segmentation model is underscored by the findings, demonstrating superior quantitative results. Precise neuron quantification is facili- tated by this model through the detection of bounding boxes in images, thereby enabling the automation of tasks such as morphological and size analysis of neuronal cells and track- ing individual neurons across ...