Skip to content
View JoelSchaust's full-sized avatar
:atom:
:atom:
7 followers · 15 following

    Organizations

    @BioMeDS

    Block or report JoelSchaust

    Block user

    Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

    You must be logged in to block users.

    Content in all repositories owned by your account will be closed.
    Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
    Report abuse

    Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

    Report abuse
    JoelSchaust/README.md

    Hi, I'm Joél

    PhD Student · Department of Ophthalmology
    Universitätsklinikum Mannheim, Heidelberg University

    Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

    Current work

    I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter uveitis cohort.

    • Deep-learning segmentation
    • Annotation methodology
    • Observer variability
    • Imaging biomarkers
    • Reproducible analysis pipelines

    Research interests

    DomainFocus
    Medical image analysisSegmentation, registration, quality control at scale
    Biomedical data scienceStudy design, evaluation metrics, statistical reporting
    Ophthalmic imagingOCT, retinal layer & lesion quantification
    MicroscopyFluorescence image analysis, single-cell segmentation
    SequencingRNA-seq, association analysis (GWAS/TWAS)

    Previously

    • BioMeds @ CCTB Würzburg — automated segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA replication analysis (Cellpose), in cooperation with the HIRI
    • Transcriptome-wide association analysis on Arabidopsis

    Languages & Tools

    Languages

    PythonRC#Bash

    Deep learning & image analysis

    PyTorchnnU-NetCellposenapariscikit-imageOpenCV

    Data & analysis

    NumPypandastidyverseggplot2JupyterR Markdown

    Infrastructure

    LinuxGitSlurmSingularityHPC

    Get in touch

    Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.

    Pinned Loading

    1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic

      In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

      Jupyter Notebook 2 1

    2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic

      Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

      Jupyter Notebook 2

    3. permGWAS_BotanypermGWAS_BotanyPublic

      Python

    4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic

      easy setup for opening DICOM images in Napari

      Jupyter Notebook 1

    , 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
     blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
JoelSchaust · GitHub
    Skip to content
    View JoelSchaust's full-sized avatar
    :atom:
    :atom:
    7
followers
 · 15
following

      Organizations
      @BioMeDS
      
Block or report JoelSchaust

      Block user
      
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

      
You must be logged in to block users.

      
Content in all repositories owned by your account will be closed.

      
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

      Report abuse
      
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

      Report abuse
      JoelSchaust/README.md
      Hi, I'm Joél
      
PhD Student · Department of Ophthalmology
      
Universitätsklinikum Mannheim, Heidelberg University

      
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

      Current work
      I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
      • Deep-learning segmentation
      • Annotation methodology
      • Observer variability
      • Imaging biomarkers
      • Reproducible analysis pipelines
      Research interests
      DomainFocus
      Medical image analysisSegmentation, registration, quality control at scale
      Biomedical data scienceStudy design, evaluation metrics, statistical reporting
      Ophthalmic imagingOCT, retinal layer & lesion quantification
      MicroscopyFluorescence image analysis, single-cell segmentation
      SequencingRNA-seq, association analysis (GWAS/TWAS)
      Previously
      • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
      • Transcriptome-wide association analysis on Arabidopsis
      Languages & Tools
      Languages
      PythonRC#Bash
      Deep learning & image analysis
      PyTorchnnU-NetCellposenapariscikit-imageOpenCV
      Data & analysis
      NumPypandastidyverseggplot2JupyterR Markdown
      Infrastructure
      LinuxGitSlurmSingularityHPC
      Get in touch
      Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
      
Pinned
Loading
      1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
        
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

        Jupyter Notebook
2

1

      2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
        
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

        Jupyter Notebook
2

      3. permGWAS_BotanypermGWAS_BotanyPublic
        Python
      4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
        
easy setup for opening DICOM images in Napari 
        Jupyter Notebook
1

      
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
JoelSchaust · GitHub
      Skip to content
      View JoelSchaust's full-sized avatar
      :atom:
      :atom:
      7
followers
 · 15
following

        Organizations
        @BioMeDS
        
Block or report JoelSchaust

        Block user
        
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

        
You must be logged in to block users.

        
Content in all repositories owned by your account will be closed.

        
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

        Report abuse
        
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

        Report abuse
        JoelSchaust/README.md
        Hi, I'm Joél
        
PhD Student · Department of Ophthalmology
        
Universitätsklinikum Mannheim, Heidelberg University

        
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

        Current work
        I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
        • Deep-learning segmentation
        • Annotation methodology
        • Observer variability
        • Imaging biomarkers
        • Reproducible analysis pipelines
        Research interests
        DomainFocus
        Medical image analysisSegmentation, registration, quality control at scale
        Biomedical data scienceStudy design, evaluation metrics, statistical reporting
        Ophthalmic imagingOCT, retinal layer & lesion quantification
        MicroscopyFluorescence image analysis, single-cell segmentation
        SequencingRNA-seq, association analysis (GWAS/TWAS)
        Previously
        • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
        • Transcriptome-wide association analysis on Arabidopsis
        Languages & Tools
        Languages
        PythonRC#Bash
        Deep learning & image analysis
        PyTorchnnU-NetCellposenapariscikit-imageOpenCV
        Data & analysis
        NumPypandastidyverseggplot2JupyterR Markdown
        Infrastructure
        LinuxGitSlurmSingularityHPC
        Get in touch
        Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
        
Pinned
Loading
        1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
          
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

          Jupyter Notebook
2

1

        2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
          
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

          Jupyter Notebook
2

        3. permGWAS_BotanypermGWAS_BotanyPublic
          Python
        4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
          
easy setup for opening DICOM images in Napari 
          Jupyter Notebook
1

        
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
JoelSchaust · GitHub
        Skip to content
        View JoelSchaust's full-sized avatar
        :atom:
        :atom:
        7
followers
 · 15
following

          Organizations
          @BioMeDS
          
Block or report JoelSchaust

          Block user
          
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

          
You must be logged in to block users.

          
Content in all repositories owned by your account will be closed.

          
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

          Report abuse
          
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

          Report abuse
          JoelSchaust/README.md
          Hi, I'm Joél
          
PhD Student · Department of Ophthalmology
          
Universitätsklinikum Mannheim, Heidelberg University

          
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

          Current work
          I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
          • Deep-learning segmentation
          • Annotation methodology
          • Observer variability
          • Imaging biomarkers
          • Reproducible analysis pipelines
          Research interests
          DomainFocus
          Medical image analysisSegmentation, registration, quality control at scale
          Biomedical data scienceStudy design, evaluation metrics, statistical reporting
          Ophthalmic imagingOCT, retinal layer & lesion quantification
          MicroscopyFluorescence image analysis, single-cell segmentation
          SequencingRNA-seq, association analysis (GWAS/TWAS)
          Previously
          • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
          • Transcriptome-wide association analysis on Arabidopsis
          Languages & Tools
          Languages
          PythonRC#Bash
          Deep learning & image analysis
          PyTorchnnU-NetCellposenapariscikit-imageOpenCV
          Data & analysis
          NumPypandastidyverseggplot2JupyterR Markdown
          Infrastructure
          LinuxGitSlurmSingularityHPC
          Get in touch
          Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
          
Pinned
Loading
          1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
            
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

            Jupyter Notebook
2

1

          2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
            
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

            Jupyter Notebook
2

          3. permGWAS_BotanypermGWAS_BotanyPublic
            Python
          4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
            
easy setup for opening DICOM images in Napari 
            Jupyter Notebook
1

          
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
JoelSchaust · GitHub
          Skip to content
          View JoelSchaust's full-sized avatar
          :atom:
          :atom:
          7
followers
 · 15
following

            Organizations
            @BioMeDS
            
Block or report JoelSchaust

            Block user
            
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

            
You must be logged in to block users.

            
Content in all repositories owned by your account will be closed.

            
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

            Report abuse
            
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

            Report abuse
            JoelSchaust/README.md
            Hi, I'm Joél
            
PhD Student · Department of Ophthalmology
            
Universitätsklinikum Mannheim, Heidelberg University

            
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

            Current work
            I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
            • Deep-learning segmentation
            • Annotation methodology
            • Observer variability
            • Imaging biomarkers
            • Reproducible analysis pipelines
            Research interests
            DomainFocus
            Medical image analysisSegmentation, registration, quality control at scale
            Biomedical data scienceStudy design, evaluation metrics, statistical reporting
            Ophthalmic imagingOCT, retinal layer & lesion quantification
            MicroscopyFluorescence image analysis, single-cell segmentation
            SequencingRNA-seq, association analysis (GWAS/TWAS)
            Previously
            • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
            • Transcriptome-wide association analysis on Arabidopsis
            Languages & Tools
            Languages
            PythonRC#Bash
            Deep learning & image analysis
            PyTorchnnU-NetCellposenapariscikit-imageOpenCV
            Data & analysis
            NumPypandastidyverseggplot2JupyterR Markdown
            Infrastructure
            LinuxGitSlurmSingularityHPC
            Get in touch
            Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
            
Pinned
Loading
            1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
              
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

              Jupyter Notebook
2

1

            2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
              
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

              Jupyter Notebook
2

            3. permGWAS_BotanypermGWAS_BotanyPublic
              Python
            4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
              
easy setup for opening DICOM images in Napari 
              Jupyter Notebook
1

            
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
JoelSchaust · GitHub
            Skip to content
            View JoelSchaust's full-sized avatar
            :atom:
            :atom:
            7
followers
 · 15
following

              Organizations
              @BioMeDS
              
Block or report JoelSchaust

              Block user
              
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

              
You must be logged in to block users.

              
Content in all repositories owned by your account will be closed.

              
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

              Report abuse
              
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

              Report abuse
              JoelSchaust/README.md
              Hi, I'm Joél
              
PhD Student · Department of Ophthalmology
              
Universitätsklinikum Mannheim, Heidelberg University

              
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

              Current work
              I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
              • Deep-learning segmentation
              • Annotation methodology
              • Observer variability
              • Imaging biomarkers
              • Reproducible analysis pipelines
              Research interests
              DomainFocus
              Medical image analysisSegmentation, registration, quality control at scale
              Biomedical data scienceStudy design, evaluation metrics, statistical reporting
              Ophthalmic imagingOCT, retinal layer & lesion quantification
              MicroscopyFluorescence image analysis, single-cell segmentation
              SequencingRNA-seq, association analysis (GWAS/TWAS)
              Previously
              • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
              • Transcriptome-wide association analysis on Arabidopsis
              Languages & Tools
              Languages
              PythonRC#Bash
              Deep learning & image analysis
              PyTorchnnU-NetCellposenapariscikit-imageOpenCV
              Data & analysis
              NumPypandastidyverseggplot2JupyterR Markdown
              Infrastructure
              LinuxGitSlurmSingularityHPC
              Get in touch
              Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
              
Pinned
Loading
              1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
                
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

                Jupyter Notebook
2

1

              2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
                
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

                Jupyter Notebook
2

              3. permGWAS_BotanypermGWAS_BotanyPublic
                Python
              4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
                
easy setup for opening DICOM images in Napari 
                Jupyter Notebook
1

              
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
JoelSchaust · GitHub
              Skip to content
              View JoelSchaust's full-sized avatar
              :atom:
              :atom:
              7
followers
 · 15
following

                Organizations
                @BioMeDS
                
Block or report JoelSchaust

                Block user
                
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

                
You must be logged in to block users.

                
Content in all repositories owned by your account will be closed.

                
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

                Report abuse
                
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

                Report abuse
                JoelSchaust/README.md
                Hi, I'm Joél
                
PhD Student · Department of Ophthalmology
                
Universitätsklinikum Mannheim, Heidelberg University

                
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

                Current work
                I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
                • Deep-learning segmentation
                • Annotation methodology
                • Observer variability
                • Imaging biomarkers
                • Reproducible analysis pipelines
                Research interests
                DomainFocus
                Medical image analysisSegmentation, registration, quality control at scale
                Biomedical data scienceStudy design, evaluation metrics, statistical reporting
                Ophthalmic imagingOCT, retinal layer & lesion quantification
                MicroscopyFluorescence image analysis, single-cell segmentation
                SequencingRNA-seq, association analysis (GWAS/TWAS)
                Previously
                • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
                • Transcriptome-wide association analysis on Arabidopsis
                Languages & Tools
                Languages
                PythonRC#Bash
                Deep learning & image analysis
                PyTorchnnU-NetCellposenapariscikit-imageOpenCV
                Data & analysis
                NumPypandastidyverseggplot2JupyterR Markdown
                Infrastructure
                LinuxGitSlurmSingularityHPC
                Get in touch
                Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
                
Pinned
Loading
                1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
                  
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

                  Jupyter Notebook
2

1

                2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
                  
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

                  Jupyter Notebook
2

                3. permGWAS_BotanypermGWAS_BotanyPublic
                  Python
                4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
                  
easy setup for opening DICOM images in Napari 
                  Jupyter Notebook
1

                
, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
JoelSchaust · GitHub
                Skip to content
                View JoelSchaust's full-sized avatar
                :atom:
                :atom:
                7
followers
 · 15
following

                  Organizations
                  @BioMeDS
                  
Block or report JoelSchaust

                  Block user
                  
Prevent this user from interacting with your repositories and sending you notifications.
Learn more about blocking users.

                  
You must be logged in to block users.

                  
Content in all repositories owned by your account will be closed.

                  
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.

                  Report abuse
                  
Contact GitHub support about this user’s behavior.
Learn more about reporting abuse.

                  Report abuse
                  JoelSchaust/README.md
                  Hi, I'm Joél
                  
PhD Student · Department of Ophthalmology
                  
Universitätsklinikum Mannheim, Heidelberg University

                  
Building imaging biomarkers from retinal OCT — from annotation protocol to trained model.

                  Current work
                  I develop quantitative image-analysis pipelines for retinal OCT and other ophthalmic imaging in a multicenter
uveitis cohort.
                  • Deep-learning segmentation
                  • Annotation methodology
                  • Observer variability
                  • Imaging biomarkers
                  • Reproducible analysis pipelines
                  Research interests
                  DomainFocus
                  Medical image analysisSegmentation, registration, quality control at scale
                  Biomedical data scienceStudy design, evaluation metrics, statistical reporting
                  Ophthalmic imagingOCT, retinal layer & lesion quantification
                  MicroscopyFluorescence image analysis, single-cell segmentation
                  SequencingRNA-seq, association analysis (GWAS/TWAS)
                  Previously
                  • BioMeds @ CCTB Würzburg — automated
segmentation of high-resolution fluorescence microscopy for single-cell Influenza A vRNA
replication analysis (Cellpose), in cooperation with the HIRI
                  • Transcriptome-wide association analysis on Arabidopsis
                  Languages & Tools
                  Languages
                  PythonRC#Bash
                  Deep learning & image analysis
                  PyTorchnnU-NetCellposenapariscikit-imageOpenCV
                  Data & analysis
                  NumPypandastidyverseggplot2JupyterR Markdown
                  Infrastructure
                  LinuxGitSlurmSingularityHPC
                  Get in touch
                  Open to exchange on segmentation benchmarking, annotation quality and clinical imaging pipelines.
                  
Pinned
Loading
                  1. BioMeDS/mudRapp-seqBioMeDS/mudRapp-seqPublic
                    
In-situ sequencing with multiple direct RNA-assisted padlock probing (mudRapp-seq)

                    Jupyter Notebook
2

1

                  2. ISS-segmentation-pipelineISS-segmentation-pipelinePublic
                    
Whole-Cell-and-Nuclear-Segmentation-in-In-situ-Sequencing-Data-pipeline

                    Jupyter Notebook
2

                  3. permGWAS_BotanypermGWAS_BotanyPublic
                    Python
                  4. Minimum-Napari-DICOM-setupMinimum-Napari-DICOM-setupPublic
                    
easy setup for opening DICOM images in Napari 
                    Jupyter Notebook
1