This topic invites original research and rigorous advances at the interface of computation and biological imaging, aligned with the mission of the Computational BioImaging section of Frontiers in Bioinformatics. We seek contributions that develop, validate, or benchmark novel computational methods, software tools, and algorithms that drive discovery from cellular to organ scales—bridging innovative computation with biological insight.

We welcome work on:
- Computer vision and machine learning for bioimage understanding, including foundation models, self-/weakly supervised learning, and interpretable AI.

- Computational optics and algorithm–hardware co-design, with emphasis on real-time and in situ analysis.

- Hardware-accelerated image analysis (GPU/TPU/FPGA), streaming pipelines, and low-latency inference at scale.

- Image acquisition and storage strategies that optimize data quality, throughput, and FAIR accessibility.

- Image restoration, registration, segmentation, and tracking, with attention to uncertainty, generalization, and reproducibility.

- Multidimensional and multiparametric analysis across space, time, spectrum, and modality (e.g., 3D/4D/5D, multimodal, single-molecule to whole-organ).

- Multiscale methods linking molecular/cellular phenotypes to tissue and organ-level organization, including graph- and topology-based approaches.

- Open-source software development, standards, and benchmarks that enable transparency, reuse, and community adoption.

- Scalable workflows for big image data annotation, curation, sharing, and lifecycle management, including privacy-preserving and federated paradigms.

Submissions should provide comprehensive methodological contributions or robust applications that clearly advance computational capabilities for biological imaging. High-value studies include algorithmic innovation, principled evaluation on representative datasets, reproducible software artifacts, and integration with experimental or clinical workflows. Work that applies routine or conventional computational techniques without substantive methodological advancement or generalizable insight falls outside the scope of this topic.

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Methods, Tools and Algorithms in Computational BioImaging

Topic Coordinator