brainchop-v2.2.0

In v2.2.0, we addressed the following minor fixes and adding a Colab example for DL training:

Fixes:

• Fix .nii extension with mri_convert (fb8cccb)

• Add Colab Example for MeshNet training (87a1ba9)

• Fix unit testing links (441f5be)

brainchop-v2.1.0

In v2.1.0, we addressed the rest of JOSS reviewers reported bugs in addition to those addressed in v2.0.1.

Fixes:

• Adjusted padding to fix Papaya MRI viewers planes visibility for screens of width > 1350 (1c9f924).

• Added two deeper Meshnet models for better brain extraction and masking accuracy (0c6f90e).

• Fixed Mocha testing for normalizeVolumeData function (60c2240).

• Modified info and warning messages text (be8e0a8).

brainchop-v2.0.1

Fixes:

• ِِAdd scrollbar to the left mini forms container (e951fbd) (#18 )

• Fix models info and warning tooltips (9f5cae7) (#19 )

brainchop-v2.0.0

With v2.0.0, it can be said that brainchop in a relatively short time exceeded the expectations as the first front-end neuroimaging tool for volumetric MRI processing. Many features have been added to brainchop functionality since first version to support data residency, 3D data rendering, preprocessing, volumetric segmentation, and postprocessing for the first time in the browser. We hope that proof of concept will pave the road for next-generation neuroimaging applications in the browser.

Features:

• Add Mocha unit testing (accac1f).

• Create draft-pdf yml file. (a3f88e3).

• Add check browser resources option. (b877464).

• Add list of verified H/W and S/W. (b877464).

brainchop-v1.4.0

Features:

• Add 3D real-time rendering of the input Nifty file. (44485e8).

• Add 3D Image processing algorithms for input denoising and enhancing. (44485e8).

brainchop-v1.3.0

Features:

• Add three.js with WebGL backend to support T1 MRI rendering and filtering regions of interest in real time. (a2c9842).

• Create three.js dat.GUI checkbox list extension to support selecting multiple segmented region to 3D visualization. (f76eee2).

• Add bar chart to plot Meshnet segmentation output volumes. (a2c9842).

• Adjust layout to add new options.(a2c9842)

brainchop-v1.2.1

Fixes:

• Fix environment parameters (2cfc9d7).

brainchop-v1.2.0

Features:

• Add 50 segmentation model to segment MRI cortical regions. Each cortical structure region is marked with a unique color/label compatible with FreeSurfer (8375a08).
• Add 104 segmentation model to segment MRI cortical and sub-cortical structures. Each structure region is marked with a unique color/label compatible with FreeSurfer (5c0e388).
• Add MRI tissue cropping pipeline to speedup the inference and lowering the memory use (8375a08).
• Add new Buffer class supports 'uint8'|'int8'|'uint16'|'int16'| 'float16' to minimize memory overhead (7ce947b) and (5c0e388).
• Fix memory leak (3f379ea).

brainchop-v1.1.0

Features:

• Add mri_convert, a pre-processing converter to support reshaping/normalizing/resampling MRI raw input data (7b6ff1c)

brainchop-v1.0.0

We are excited to announce the first release of brainchop. This brings automatic 3D MRI segmentation capability to neuroimaging. You can use the online front-end brainchop.org or use it in the offline mode. Offline setup instructions are available on brainchop Wiki.

This package:

• Supports inference on 3D volumetric MRI data with WebGL.
• Supports full brain volume inference and subcube inference.
• Supports post-processing and noise removal.
• Supports saving resulting MRI labels in the Nifti format.
• Supports pre-processing and normalization
• Supports importing compatible pre-trained custom models in tfjs.

We welcome your feedback to help shape our priorities for brainchop. We also welcome contributors familiar with tfjs and neuroimaging applications who are interested in getting involved in expanding brainchop model zoo.

Looking forward to your contribution!