Software
This is a short description of BioVIsion's software stack. Feel free to browse our GitHub page to learn more.
BIOENCODER
BioEncoder is a toolkit for supervised metric learning to i) learn and extract features from images, ii) enhance biological image classification, and iii) identify the features most relevant to classification. Designed for diverse and complex datasets, the package and the available metric losses can handle unbalanced classes and subtle phenotypic differences more effectively than non-metric approaches. The package includes taxon-agnostic data loaders, custom augmentation techniques, hyperparameter tuning through YAML configuration files, and rich model visualizations, providing a comprehensive solution for high-throughput analysis of biological images.
ALPACA
ALPACA provides fast landmark transfer from a 3D model and its associated landmark set to target 3D model(s) through pointcloud alignment and deformable mesh registration. Optimal set of parameters that gives the best correspondence can be investigated in single alignment mode, and then applied to a number of 3D models in batch mode. ALPACA is a core component of the SlicerMorph project.
DEEP BRYO
DeepBryo is a web application for deep learning-based morphometric characterization of cheilostome bryozoans. DeepBryo requires a single image as input and performs measurements automatically using instance segmentation algorithms. DeepBryo is capable of detecting objects belonging to six classes and outputting fourteen morphological shape measurements for each object based on the inferred segmentation maps. The users can visualize the predictions, check for errors, and directly filter model outputs on the web browser. Measurements can then be downloaded as a comma-separated values file.
ML - MORPH
ml-morph is a tool that can be used to collect high-dimensional morphometric data in two-dimensional images of semi-rigid biological structures. It allows for dense and accurate landmarking at low cost, high speed and with minimal impact on specimens.
https://github.com/agporto/ml-morph
APPENDOMETER
Appendometer is a CLI tool for machine-learning-based morphometric characterization of Drosophila leg elements. It performs landmark prediction in Drosophila images using the ml-morph pipeline and saves the output to TPS files.
STEGINATOR
Steginator is a CLI tool for deep-learning-based morphometric characterization of Steginoporella magnifica zooids. It performs zooid detection using the DeepBryo pipeline and landmark prediction using the ml-morph pipeline and saves the output to TPS files.
https://github.com/agporto/Steginator
PYCPD (Contributor)
PyCPD is a pure numpy implementation of the coherent point drift CPD algorithm by Myronenko and Song for use by the python community. It provides three registration methods for point clouds: 1) Scale and rigid registration; 2) Affine registration; and 3) Gaussian regularized non-rigid registration.
https://github.com/siavashk/pycpd