Synonyms
Minimum projection
Maximum projection
Maximum intensity projection
Mean projection

FastSME

Description

FastSME: Faster and Smoother Manifold Extraction From 3D Stack.

3D image stacks are routinely acquired to capture data that lie on undulating 3D manifolds yet processed in 2D by biologists. Algorithms to reconstruct the specimen morphology into a 2D representation from the 3D image volume are employed in such scenarios. In this paper, we present FastSME, which offers several improvements on the baseline SME algorithm which enables accurate 2D representation of data on a manifold from 3D volumes, however is computationally expensive. The improvements are achieved in terms of processing speed (3X-10X speed-up depending on image size), minimizing sensitivity to initialization, and also increases local smoothness of the recovered manifold resulting in better reconstructed 2D composite image. We compare the proposed FastSME against the baseline SME as well as other accessible state-of-the-art tools on synthetic and real microscopy data. Our evaluation on multiple metrics demonstrates the efficiency of the presented method in maintaining fidelity of manifold shape and hence specimen morphology.

has topic
has function

SME

Description

Smooth 2D Manifold Extraction (SME).

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks. We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy.

has topic
has function
SME

clij - GPU-acceleration for ImageJ

Description

clij is an ImageJ/Fiji plugin allowing you to run GPU-accelerated code from within Fijis script editor (e.g. macro and jython). CLIJ is based on ClearCLImglib2 and SciJava. It contains components for image filtering, thresholding, spatial transforms, projections, binary image processing and basic signal measurements.

Minimum cost Z surface projection

Description

This plugin detects a minimum cost z-surface in a 3D volume. A z surface is a topographic map indicating the altitude z as a function of the position (x,y) in the image. The cost of the surface depends on pixel intensity the surface is going through. This plugin find the z-surface with the lowest intensity in an image.

has function

CSBDeep, a toolbox for Content-aware Image Restoration (CARE) in Fiji

Description

Deep learning for fluorescence image restoration (denoising, deconvolution). Requires training on your data set but the procedure is described.

CARE

LIF Projector

Description

This macro is similar to the LIF_Extractor, but it will output Z-projection of each Z-stack. You can choose the type of projection in addition to the other options. Requires Bio-Formats plugin

has function

Tube un-winder

Description

This macro can be used to un-wide a tubular structure and flatten its surface (like peeling of and flattening the skin of a banana). The macro can only process a single channel 3D stack but it is easy to process multiple channels by exporting and importing ROI manager selections. Technically the macro computes the radial average intensity projection inside a ring centred on the radial symmetry axis of the object. The final image is a radial mapping of the intensity (radial angle along X, axial length along Y).

The example image is available in the documentation link. 

has function

Icy Projection

has function
need a thumbnail

Intensity Projection

has function
need a thumbnail