Revista Sextante

A Spiral-Based Methodology Applied to Cell Image Analysis

Margarita Gamarra Acosta

Ingeniería Electrónica, Politécnico de la Costa Atlántica, Barranquilla, Colombia

Evert De los Ríos Trujillo

Ingeniería Electrónica, Universidad del Magdalena, Santa Marta, Colombia

José Escorcia-Gutierrez

Centro de Investigaciones, Escuela Naval de Suboficiales A.R.C. “Barranquilla”, Barranquilla, Colombia

Keywords: Bioinformatics, cell image, image processing, spiral model, image segmentation, feature extraction, biomedical imaging, software methodology

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Abstract

Rapid developments in microscopy, computational technologies, digital image processing, and bioinformatics have substantially increased the amount of information that can be extracted from cellular images. Despite these advances, many cell-image analysis systems remain difficult for non-specialist users because they require expertise in image processing, programming, algorithm configuration, and statistical interpretation. Consequently, successful biomedical image-analysis projects often require continuous collaboration among biologists, laboratory specialists, computer scientists, engineers, and software developers. This article presents an expanded spiral-based methodology for developing software solutions for cell-image analysis. The approach integrates the iterative principles of the spiral software-development model with the principal stages of digital image processing, including image acquisition, preprocessing, segmentation, feature extraction, classification, and statistical interpretation. Each processing stage is examined through recurring phases of analysis, evaluation, modeling, development, verification, and expert validation. The methodology emphasizes continuous participation by biological experts and technical specialists throughout the development process. This collaboration allows algorithms, parameters, features, and classification strategies to be progressively adjusted according to the characteristics of the biological problem. The iterative structure is particularly useful when microscopic images present complex conditions such as overlapping cells, variable illumination, heterogeneous morphology, noise, or differences in image acquisition. The methodology can be applied to different biomedical imaging applications and is especially suitable for projects in which requirements evolve during experimentation. A case involving respiratory syncytial virus-related cellular analysis demonstrates how a spiral process can organize image acquisition, segmentation, feature extraction, and analytical tasks while maintaining close interaction between computational and biological experts.