Synthetic image generation

This workflow describes a deep-learning based pipeline for reliable single-organoid segmentation and tracking in 2D+t high-resolution brightfield microscopy of mouse mammary epithelial organoids. The pipeline involves a four-layer U-Net to infer semantic segmentation predictions, adaptive morphological filtering to establish candidate organoid instances, and a shape-similarity-constrained, instance-segmentation-correcting tracking step to associate the corresponding organoid instances in time.

It is particularly focused on automatically detecting an organoid located approximately in the center of the first frame and track all its subsequent instances in the remaining frames, emphasizing on accurate organoid boundary delineation. Furthermore, segmentation network was trained using plausible pix2pixHD-generated bioimage data. Syntheric image simulator code and data are also available here.

Wavelet Toolbox™ provides apps and functions for the time-frequency analysis of signals and multiscale analysis of images.

Software for computing single molecule localization accuracies and resolution measures

The FandPLimitTool is a GUI based software module that allows users to calculate the limits to the accuracy with which parameters can be estimated from single molecule imaging data. The software supports calculation of limits for the 2D/3D location estimation problem and the 2D/3D distance-estimation/resolution problem. The location estimation problem is concerned with the task of determining the position of a single molecule and the distance-estimation/resolution problem is concerned with the task of determining the distance of separation between two single molecules. The user can calculate limits for a variety of imaging scenarios.

CompuCell3D is a flexible scriptable modeling environment, which allows the rapid construction of sharable Virtual Tissue in-silico simulations of a wide variety of multi-scale, multi-cellular problems including angiogenesis, bacterial colonies, cancer, developmental biology, evolution, the immune system, tissue engineering, toxicology and even non-cellular soft materials. CompuCell3D models have been used to solve basic biological problems, to develop medical therapies, to assess modes of action of toxicants and to design engineered tissues. CompuCell3D intuitive and make Virtual Tissue modeling accessible to users without extensive software development or programming experience.

It uses Cellular Potts Model to model cell behavior.

NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can:

• Get started with established pre-trained networks using built-in tools;
• Adapt existing networks to your imaging data;
• Quickly build new solutions to your own image analysis problems.