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balbasty/README.md

PyTorch extensions

These repositories are small self-contained tools written in pure PyTorch, that I have found useful in many projects.

They are (relatively) stable, as backward-compatible as possible with respect to PyTorch versions, and can be used as core dependencies to higher level projects.

PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠

Note

The last package, jitfields, reimplements many of the utilities from the other core packages, but does it directly in CUDA/C++.

The CUDA/C++ sources are compiled just-in-time using cupy and cppyy.

🧠 Machine Learning for NeuroImaging

These packages underpin my research in medical image computing.

In general, my aim is to write a set of mid-level packages that specialize in various tasks (data augmentation, network architectures, modality-specific tasks, etc.).

PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴

Numpy tools

PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴

Matlab tools

PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢

Tensorflow tools

PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned Loading

  1. nitorchnitorchPublic

    Neuroimaging in PyTorch

    Python 100 15

  2. torch-interpoltorch-interpolPublic

    High-order spline interpolation in PyTorch

    Python 76 6

  3. multi-biasmulti-biasPublic

    Fit a multi-view bias field

    MATLAB 1

  4. cornucopiacornucopiaPublic

    An abundance of augmentation layers

    Python 20 9

  5. super-resolutionsuper-resolutionPublic

    Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB 1 1

  6. brudfors/UniResbrudfors/UniResPublic

    Unified super-resolution and denoising of medical images in PyTorch

    Python 94 12

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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


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 · 1
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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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59
followers
 · 1
following

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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


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 · 1
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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


, 'i');
if (__m === '*' || __re.test(location.href)) {
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 · 1
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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12


, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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View balbasty's full-sized avatar
59
followers
 · 1
following

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balbasty/README.md
 PyTorch extensions
These repositories are small self-contained tools written in pure PyTorch,
that I have found useful in many projects.
They are (relatively) stable, as backward-compatible as possible with
respect to PyTorch versions, and can be used as core dependencies to
higher level projects.
PackageDescriptionReadiness
torch-boundsBoundary conditions (circulant, mirror, reflect) and real transforms (DCT, DST)🟢
torch-interpolHigh-order spline interpolation🟢
torch-distmapEuclidean distance transform🟢
torch-relayBackward-compatible PyTorch functions (work-in-progress)🔴
torch-diffeoScaling-and-squaring and Geodesic Shooting layers in PyTorch (work-in-progress)🟠
jitfieldsFast functions for dense scalar and vector fields, implemented using just-in-time compilation🟠
Note
The last package, jitfields, reimplements many of the utilities from the other core
packages, but does it directly in CUDA/C++.
The CUDA/C++ sources are compiled
just-in-time using cupy
and cppyy.
🧠 Machine Learning for NeuroImaging
These packages underpin my research in medical image computing.
In general, my aim is to write a set of mid-level packages that
specialize in various tasks (data augmentation, network architectures,
modality-specific tasks, etc.).
PackageDescriptionReadiness
cornucopiaAn abundance of augmentation layers🟢
nitorchAn (overweight and poorly maintained) package for everything neuroimaging🟠
synthsurfSurface-based image synthesis and PyTorch utilities for triangular surfaces🟠
synthsplineSynthetic tubular structures (vessels, axons) for NN pretraining🟠
cassettaA deep learning toolbox (under early development)🔴
braindataprepDownload, bidsify and preprocess public datasets (work-in-progress)🔴
 Numpy tools
PackageDescriptionReadiness
variational_stapleSTAPLE and variants🟢
optimal_affineBuild optimal "subject to mean space" affines from "subject to subject" pairwise affines🟢
metricsA bunch of metrics🔴
 Matlab tools
PackageDescriptionReadiness
spm_mni_alignSPM toolbox to align an image to SPM's template space🟠
multi-biasFit a multi-view bias field🟢
super-resolutionMTV-based denoising/super-resolution🟢
cmaps(Some) Matplotlib colormaps in Matlab🟢
 Tensorflow tools
PackageDescriptionReadiness
tfaffine Affine matrices encoded in their Lie algebra, in tensorflow🟢

Pinned
Loading
  1. nitorchnitorchPublic
    
Neuroimaging in PyTorch

    Python
100

15

  2. torch-interpoltorch-interpolPublic
    
High-order spline interpolation in PyTorch

    Python
76

6

  3. multi-biasmulti-biasPublic
    
Fit a multi-view bias field

    MATLAB
1

  4. cornucopiacornucopiaPublic
    
An abundance of augmentation layers

    Python
20

9

  5. super-resolutionsuper-resolutionPublic
    
Reimplement MTV-based denoising/super-resolution using a reweighted least-squares approach

    MATLAB
1

1

  6. brudfors/UniResbrudfors/UniResPublic
    
Unified super-resolution and denoising of medical images in PyTorch

    Python
94

12