This repository contains scripts is used to simulate confocal fluorescence microscopy images from the results of a finite element reaction-diffusion model of calcium diffusing in the intracellular space of a cardiomyocyte. The simulated images are then used to evaluate the performance of the CaCLEAN algorithm, which seeks to identify the locations of calcium release sites in experimental imaging of live cardiomyocytes.
For more information, please see the corresponding manuscript: Detecting RyR clusters with CaCLEAN: influence of spatial distribution and structural heterogeneity
Also see the original paper proposing the CaCLEAN algorithm: An adaptation of astronomical image processing enables characterization and functional 3D mapping of individual sites of excitation-contraction coupling in rat cardiac muscle
This set of scripts are designed to perform operations on the results of the CardiacCalcium_FiniteElement model. Alternatively, results of the finite element models may be obtained from the author's FigShare archives at [TODO: insert DOI]. The CaCLEAN Evaluator also depends on the CaCLEAN algorithm. The scripts currently expect these repositories to be cloned into the same parent directory. Child dependencies for these projects may also need to be satisfied.
The Python script SimulateMicroscopy.py reads in the finite element nodal values and interpolates the fluorophore-bound calcium (FCa) field results onto a regular grid (53nm resolution in all directions) using discrete natural neighbor (Sibson) interpolation. These results are convolved with a point spread function to produce optical blurring typical of confocal microscopy. They are then downsampled to produce 22 images with 215 nm resolution in the image x and y plane and 5 ms temporal resolution. Light noise (SNR=100) is added to the image data and a background image normalised to the same image resolution and the FCa initial values. Pixel locations in each image are checked against a surface model of the cell membrane to construct a boolean mask for the intracellular space.
The simulated microscopy results and known modeled RyR locations are saved in a Matlab .mat file, to be used by the CaCLEAN Evaluator.
Python modules used:
The TestCaCLEAN_SimulatedMicroscopyResults.m Matlab script operates on the results of the Confocal Microscopy Simulator using the CaCLEAN algorithm.
A statistical classification approach was used to assess the performance of RyR cluster detection using CaCLEAN. Modeled cluster centers within the admissible window were considered the actual / ground truth class: TP (ground truth). CaCLEAN detection results were considered the predicted class. Detected RyR cluster sites were defined as determined by the CaCLEAN CRUProps function, which segments cluster regions using Matlab’s built-in watershed algorithm and identifies centroids of segmented regions.
For each modeled cluster location, a TP (detected) classification was assigned if a TP (ground truth) cluster center lied within an available segmented CaCLEAN cluster region (or within a 1 pixel tolerance). When more than one TP (ground truth) fell within a CaCLEAN-detected cluster region, the detected cluster with the nearest centroid to the TP (ground truth) location was marked TP (detected). After classification as TP (detected), the associated CaCLEAN-detected site would be removed from the list of available matches. After iterating through the TP (ground truth) clusters, remaining TP (ground truth) unmatched with detected clusters were classified as false negatives (FN). Remaining CaCLEAN-detected sites unmatched with TP (ground truth) were classified as false positives (FP).
Matlab dependencies used in this project:
- shadedErrorBar
- colormap
- CaCLEAN
- smoothn(required by CaCLEAN)
- FMINSEARCHBND(required by CaCLEAN)
- David Ladd - dladd
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
- Systems Biology Laboratory at the University of Melbourne
- Centre of Excellence in Convergent Bio-Nano Science and Technology
- Cell Structure and Mechanobiology Group at the University of Melbourne