SVdetection

SVdetection is a Python library designed for the detection and analysis of single-molecule fluorescence data, particularly in the context of single-molecule localization microscopy (SMLM) techniques such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM). The toolkit provides a modular framework for processing raw fluorescence images to extract precise localization information from individual fluorescent molecules.

The library is built on top of the SciPy and NumPy scientific computing libraries, offering efficient algorithms for peak detection, background subtraction, and localization fitting. SVdetection implements several advanced methods, including Gaussian fitting and machine learning-based approaches, to improve the accuracy and reliability of molecule localization. It also includes utilities for handling common artifacts, such as background noise and photobleaching, which can affect data quality.

SVdetection is particularly useful for researchers working in biological imaging, where high-resolution visualization of cellular structures is required. By enabling precise localization of fluorescent markers, the library facilitates the reconstruction of super-resolution images that exceed the diffraction limit of light microscopy. The modular design allows users to customize workflows, making it adaptable to different experimental setups and imaging modalities.

The software is open-source and distributed under the MIT License, encouraging community contributions and collaboration. It is widely used in academic research and has been integrated into larger bioimaging pipelines. Documentation and tutorials are available to assist users in implementing SVdetection for their specific applications, though familiarity with Python and basic image processing concepts is recommended.