Radiologisches Bild-zu-detailliertem-Bericht-Konverter

Fortgeschritten

Dies ist ein Document Extraction, Multimodal AI-Bereich Automatisierungsworkflow mit 12 Nodes. Hauptsächlich werden Code, Wait, Gmail, Webhook, HttpRequest und andere Nodes verwendet. Konvertieren Sie radiologische Bilder mithilfe von GPT-4 Vision und PDF-Mail in patientenfreundliche Berichte

Voraussetzungen
  • Google-Konto + Gmail API-Anmeldedaten
  • HTTP Webhook-Endpunkt (wird von n8n automatisch generiert)
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • Google Sheets API-Anmeldedaten
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "8DYI99J1q8APXjWY",
  "meta": {
    "instanceId": "dd69efaf8212c74ad206700d104739d3329588a6f3f8381a46a481f34c9cc281",
    "templateCredsSetupCompleted": true
  },
  "name": "Radiology Image to Detailed Report Converter",
  "tags": [],
  "nodes": [
    {
      "id": "89d05f4e-32c8-4ce2-aabb-26068052a70b",
      "name": "Upload Image Trigger",
      "type": "n8n-nodes-base.webhook",
      "position": [
        180,
        -120
      ],
      "webhookId": "radiology-upload-webhook",
      "parameters": {
        "path": "radiology-upload",
        "options": {},
        "httpMethod": "POST"
      },
      "typeVersion": 2
    },
    {
      "id": "395b8ea6-f7aa-4d47-a73c-22ab891674ec",
      "name": "Bilddaten extrahieren",
      "type": "n8n-nodes-base.code",
      "position": [
        400,
        -120
      ],
      "parameters": {
        "jsCode": "// Extract image and patient data from webhook\nconst data = $input.first().json;\n\nreturn [{\n  json: {\n    patient_name: data.patient_name || 'Patient',\n    patient_id: data.patient_id || 'N/A',\n    scan_type: data.scan_type || 'X-Ray',\n    body_part: data.body_part || 'Chest',\n    image_url: data.image_url,\n    image_base64: data.image_base64,\n    doctor_name: data.doctor_name || 'Dr. Smith',\n    scan_date: data.scan_date || new Date().toISOString().split('T')[0],\n    urgency: data.urgency || 'routine'\n  }\n}];"
      },
      "typeVersion": 2
    },
    {
      "id": "090ab8d4-4e1c-4c23-9fe8-f6c74b850a8a",
      "name": "Radiologie-Bild mit KI analysieren",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        620,
        -120
      ],
      "parameters": {
        "url": "https://api.openai.com/v1/chat/completions",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"model\": \"gpt-4-vision-preview\",\n  \"messages\": [\n    {\n      \"role\": \"system\",\n      \"content\": \"You are a radiology expert who explains medical scans in simple, patient-friendly language. Analyze the radiology image and provide: 1) What the scan shows in simple terms 2) Any notable findings 3) What this means for the patient 4) Next steps if any. Be reassuring and avoid medical jargon. Always recommend consulting with their doctor.\"\n    },\n    {\n      \"role\": \"user\",\n      \"content\": [\n        {\n          \"type\": \"text\",\n          \"text\": \"Please analyze this {{ $json.scan_type }} scan of the {{ $json.body_part }} and explain the findings in patient-friendly terms.\"\n        },\n        {\n          \"type\": \"image_url\",\n          \"image_url\": {\n            \"url\": \"{{ $json.image_base64 ? 'data:image/jpeg;base64,' + $json.image_base64 : $json.image_url }}\"\n          }\n        }\n      ]\n    }\n  ],\n  \"max_tokens\": 1000,\n  \"temperature\": 0.3\n}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer {{ $credentials.openaiApi.apiKey }}"
            },
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "47095b28-484a-47ce-b450-6dd0d719d989",
      "name": "KI-Analyse verarbeiten",
      "type": "n8n-nodes-base.code",
      "position": [
        840,
        -120
      ],
      "parameters": {
        "jsCode": "// Process OpenAI response and structure the report data\nconst aiResponse = $input.first().json;\nconst patientData = $('Extract Image Data').first().json;\n\nconst aiAnalysis = aiResponse.choices[0].message.content;\n\n// Structure the analysis into sections\nconst sections = aiAnalysis.split('\\n\\n');\nlet findings = '';\nlet explanation = '';\nlet nextSteps = '';\n\n// Try to parse the AI response into structured sections\nsections.forEach(section => {\n  if (section.toLowerCase().includes('findings') || section.toLowerCase().includes('shows')) {\n    findings += section + ' ';\n  } else if (section.toLowerCase().includes('means') || section.toLowerCase().includes('indicates')) {\n    explanation += section + ' ';\n  } else if (section.toLowerCase().includes('next') || section.toLowerCase().includes('recommend')) {\n    nextSteps += section + ' ';\n  }\n});\n\n// If structured parsing didn't work well, use the full response\nif (!findings && !explanation) {\n  findings = aiAnalysis.substring(0, aiAnalysis.length / 2);\n  explanation = aiAnalysis.substring(aiAnalysis.length / 2);\n}\n\nreturn [{\n  json: {\n    ...patientData,\n    ai_analysis: aiAnalysis,\n    findings: findings.trim() || 'Analysis completed',\n    explanation: explanation.trim() || 'Please consult with your doctor for detailed explanation',\n    next_steps: nextSteps.trim() || 'Follow up with your healthcare provider as recommended',\n    report_generated: new Date().toISOString(),\n    confidence_note: 'This AI analysis is for informational purposes only. Always consult your doctor for medical advice.'\n  }\n}];"
      },
      "typeVersion": 2
    },
    {
      "id": "223aebb0-5f1e-40fb-bc00-ed70a4cba515",
      "name": "PDF-Bericht generieren",
      "type": "n8n-nodes-base.code",
      "position": [
        1060,
        -120
      ],
      "parameters": {
        "jsCode": "// Generate HTML template for PDF conversion\nconst data = $input.first().json;\n\nconst htmlReport = `\n<!DOCTYPE html>\n<html>\n<head>\n    <style>\n        body { font-family: Arial, sans-serif; line-height: 1.6; color: #333; margin: 40px; }\n        .header { text-align: center; border-bottom: 3px solid #4CAF50; padding-bottom: 20px; margin-bottom: 30px; }\n        .logo { font-size: 24px; font-weight: bold; color: #4CAF50; }\n        .patient-info { background-color: #f8f9fa; padding: 20px; border-radius: 8px; margin: 20px 0; }\n        .section { margin: 25px 0; }\n        .section-title { font-size: 18px; font-weight: bold; color: #2c3e50; border-left: 4px solid #4CAF50; padding-left: 15px; margin-bottom: 15px; }\n        .findings { background-color: #e8f5e8; padding: 20px; border-radius: 8px; border-left: 4px solid #4CAF50; }\n        .explanation { background-color: #fff3e0; padding: 20px; border-radius: 8px; border-left: 4px solid #ff9800; }\n        .next-steps { background-color: #e3f2fd; padding: 20px; border-radius: 8px; border-left: 4px solid #2196f3; }\n        .disclaimer { background-color: #ffebee; padding: 15px; border-radius: 8px; font-size: 14px; border: 1px solid #f44336; margin-top: 30px; }\n        .footer { text-align: center; margin-top: 40px; font-size: 12px; color: #666; }\n        .date { color: #666; font-size: 14px; }\n    </style>\n</head>\n<body>\n    <div class=\"header\">\n        <div class=\"logo\">🏥 Medical Imaging Report</div>\n        <h2>Patient-Friendly Radiology Report</h2>\n        <div class=\"date\">Generated: ${new Date(data.report_generated).toLocaleDateString()}</div>\n    </div>\n    \n    <div class=\"patient-info\">\n        <h3>👤 Patient Information</h3>\n        <p><strong>Patient Name:</strong> ${data.patient_name}</p>\n        <p><strong>Patient ID:</strong> ${data.patient_id}</p>\n        <p><strong>Scan Type:</strong> ${data.scan_type}</p>\n        <p><strong>Body Part:</strong> ${data.body_part}</p>\n        <p><strong>Scan Date:</strong> ${data.scan_date}</p>\n        <p><strong>Ordering Doctor:</strong> ${data.doctor_name}</p>\n    </div>\n    \n    <div class=\"section\">\n        <div class=\"section-title\">🔍 What We Found</div>\n        <div class=\"findings\">\n            <p>${data.findings}</p>\n        </div>\n    </div>\n    \n    <div class=\"section\">\n        <div class=\"section-title\">💡 What This Means</div>\n        <div class=\"explanation\">\n            <p>${data.explanation}</p>\n        </div>\n    </div>\n    \n    <div class=\"section\">\n        <div class=\"section-title\">📋 Next Steps</div>\n        <div class=\"next-steps\">\n            <p>${data.next_steps}</p>\n        </div>\n    </div>\n    \n    <div class=\"disclaimer\">\n        <h4>⚠️ Important Disclaimer</h4>\n        <p>${data.confidence_note}</p>\n        <p>This report is generated by AI technology to help you understand your scan results. It should not replace professional medical consultation. Please discuss these findings with your healthcare provider.</p>\n    </div>\n    \n    <div class=\"footer\">\n        <p>Report generated by AI-Powered Radiology Assistant</p>\n        <p>For medical questions, contact your healthcare provider</p>\n    </div>\n</body>\n</html>\n`;\n\nreturn [{\n  json: {\n    ...data,\n    html_report: htmlReport,\n    report_filename: `Radiology_Report_${data.patient_name.replace(/\\s+/g, '_')}_${data.scan_date}.pdf`\n  }\n}];"
      },
      "typeVersion": 2
    },
    {
      "id": "4deecdc3-3b5a-4987-a62d-43f7034431c2",
      "name": "In PDF konvertieren",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1280,
        -120
      ],
      "parameters": {
        "url": "https://api.html-css-to-pdf.com/v1/generate",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"html\": \"{{ $json.html_report }}\",\n  \"options\": {\n    \"format\": \"A4\",\n    \"margin\": {\n      \"top\": \"20mm\",\n      \"right\": \"15mm\",\n      \"bottom\": \"20mm\",\n      \"left\": \"15mm\"\n    },\n    \"displayHeaderFooter\": false\n  }\n}",
        "sendBody": true,
        "sendHeaders": true,
        "specifyBody": "json",
        "headerParameters": {
          "parameters": [
            {
              "name": "Authorization",
              "value": "Bearer {{ $credentials.pdfApi.apiKey }}"
            },
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "581fef88-4096-4193-b71e-9893fd684d1f",
      "name": "Bericht in Datenbank speichern",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        1720,
        -120
      ],
      "parameters": {
        "columns": {
          "value": {
            "pdf_url": "={{ $json.download_url }}",
            "body_part": "={{ $('Generate PDF Report').first().json.body_part }}",
            "scan_date": "={{ $('Generate PDF Report').first().json.scan_date }}",
            "scan_type": "={{ $('Generate PDF Report').first().json.scan_type }}",
            "timestamp": "={{ $now.toISO() }}",
            "patient_id": "={{ $('Generate PDF Report').first().json.patient_id }}",
            "patient_name": "={{ $('Generate PDF Report').first().json.patient_name }}",
            "report_status": "Generated Successfully"
          },
          "schema": [
            {
              "id": "timestamp",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Timestamp",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "patient_name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Patient Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "patient_id",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Patient ID",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "scan_type",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Scan Type",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "body_part",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Body Part",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "scan_date",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Scan Date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "report_status",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Report Status",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "pdf_url",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "PDF URL",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow"
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "Reports_Log",
          "cachedResultName": "Reports Log"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "YOUR_REPORTS_SHEET_ID",
          "cachedResultName": "Radiology Reports"
        },
        "authentication": "serviceAccount"
      },
      "credentials": {
        "googleApi": {
          "id": "ScSS2KxGQULuPtdy",
          "name": "Google Sheets- test"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "f2025595-5b43-48dd-a586-351054d7d6d3",
      "name": "Bericht an Patienten senden",
      "type": "n8n-nodes-base.gmail",
      "position": [
        1940,
        -120
      ],
      "webhookId": "4a00c62f-eac2-46c6-9013-61a94e903084",
      "parameters": {
        "sendTo": "={{ $('Extract Image Data').first().json.patient_email || 'patient@example.com' }}",
        "message": "=<h2>Your Radiology Report is Ready! 🏥</h2><br><br>Dear {{ $('Generate PDF Report').first().json.patient_name }},<br><br>Your {{ $('Generate PDF Report').first().json.scan_type }} scan report is now available. This patient-friendly report explains your scan results in easy-to-understand language.<br><br><strong>Scan Details:</strong><br>• Type: {{ $('Generate PDF Report').first().json.scan_type }}<br>• Body Part: {{ $('Generate PDF Report').first().json.body_part }}<br>• Date: {{ $('Generate PDF Report').first().json.scan_date }}<br><br><strong>Key Findings:</strong><br>{{ $('Process AI Analysis').first().json.findings }}<br><br>📎 <strong>Your complete report is attached as a PDF.</strong><br><br>❗ <strong>Important:</strong> This AI-generated report is for informational purposes. Please discuss these results with {{ $('Generate PDF Report').first().json.doctor_name }} or your healthcare provider.<br><br>If you have any questions, please contact your healthcare provider.<br><br>Best regards,<br>Medical Imaging Department",
        "options": {},
        "subject": "🏥 Your Radiology Report is Ready - {{ $('Generate PDF Report').first().json.patient_name }}"
      },
      "credentials": {
        "gmailOAuth2": {
          "id": "PcTqvGU9uCunfltE",
          "name": "Gmail account - test"
        }
      },
      "typeVersion": 2.1
    },
    {
      "id": "badb5a4d-2b43-47a9-b1c8-12db0f4e7a5b",
      "name": "Antwort zurückgeben",
      "type": "n8n-nodes-base.code",
      "position": [
        2160,
        -120
      ],
      "parameters": {
        "jsCode": "// Return success response with report details\nconst reportData = $('Generate PDF Report').first().json;\nconst pdfData = $('Convert to PDF').first().json;\n\nreturn [{\n  json: {\n    status: 'success',\n    message: 'Radiology report generated successfully',\n    patient_name: reportData.patient_name,\n    scan_type: reportData.scan_type,\n    body_part: reportData.body_part,\n    report_generated: reportData.report_generated,\n    pdf_url: pdfData.download_url,\n    findings_summary: reportData.findings.substring(0, 200) + '...',\n    next_steps: reportData.next_steps,\n    disclaimer: reportData.confidence_note\n  }\n}];"
      },
      "typeVersion": 2
    },
    {
      "id": "7b5c9eb3-37c2-43f8-a0f1-f95554b6c9ef",
      "name": "Workflow-Übersicht",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        340,
        -600
      ],
      "parameters": {
        "width": 400,
        "height": 340,
        "content": "## 🏥 Radiology Image to Report Converter\n\n### Features:\n• AI-powered image analysis\n• Patient-friendly language\n• Professional PDF reports\n• Email delivery\n• Database logging\n• Webhook triggered\n\n### How to use:\nSend POST to webhook with image data"
      },
      "typeVersion": 1
    },
    {
      "id": "925f5199-dbac-427b-a896-228e864f524b",
      "name": "Erforderliche Einrichtung",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1080,
        -540
      ],
      "parameters": {
        "color": 3,
        "width": 300,
        "height": 200,
        "content": "## ⚙️ Setup Required\n\n1. OpenAI API credentials (GPT-4 Vision)\n2. PDF conversion service\n3. Gmail account for sending\n4. Google Sheets for logging\n5. Update YOUR_REPORTS_SHEET_ID"
      },
      "typeVersion": 1
    },
    {
      "id": "e5159a65-1ba2-4bc0-99dc-d89cef310932",
      "name": "Auf PDF warten",
      "type": "n8n-nodes-base.wait",
      "position": [
        1500,
        -120
      ],
      "webhookId": "25e9fc56-abe3-4dbc-9d2d-edcf098f8ecc",
      "parameters": {},
      "typeVersion": 1.1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "307925d2-0fa2-459f-a60c-af7b0ae0bbb3",
  "connections": {
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}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Dokumentenextraktion, Multimodales KI

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes12
Kategorie2
Node-Typen7
Schwierigkeitsbeschreibung

Für erfahrene Benutzer, mittelkomplexe Workflows mit 6-15 Nodes

Autor
Oneclick AI Squad

Oneclick AI Squad

@oneclick-ai

The AI Squad Initiative is a pioneering effort to build, automate and scale AI-powered workflows using n8n.io. Our mission is to help individuals and businesses integrate AI agents seamlessly into their daily operations from automating tasks and enhancing productivity to creating innovative, intelligent solutions. We design modular, reusable AI workflow templates that empower creators, developers and teams to supercharge their automation with minimal effort and maximum impact.

Externe Links
Auf n8n.io ansehen

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Kategorien

Kategorien: 34