AI SaaS for Dental Implant Diagnosis Using DICOM CT Scans
Budget: $250 – $750 USD
AI SaaS for Dental Implant Diagnosis Using DICOM CT Scans
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Project Overview:
We are building a web-based SaaS platform that uses Artificial Intelligence to analyze dental CT scans (DICOM format) and support implantology diagnosis.
The platform should:
• Allow users (dentists/clinics) to upload DICOM (.dcm) files from dental CT scans.
• Use AI to detect caries, cysts, and available bone volume based on visual patterns (color and location).
• Enable the dentist to simulate dental implant placement in a 3D environment.
• Be trained and validated with the support of a professional implantologist, who will provide labeled data.
This project is in its early stages and will start with an MVP.
⸻
Technical Requirements:
Frontend:
• React.js (preferred)
• Integration with OHIF Viewer or Cornerstone.js for DICOM rendering
• 3D implant simulation (Three.js or similar)
Backend:
• Python + FastAPI or Flask
• File upload system (DICOM)
• API to trigger inference from trained AI model
AI/ML:
• Medical image segmentation using PyTorch or TensorFlow
• Preferred model: nnU-Net or MONAI
• Input: DICOM or preprocessed volume data
• Output: Segmented zones (caries, cysts, bone availability)
Data Format:
• Input: .dcm (DICOM format)
• Annotations: Provided by an implantologist using 3D Slicer or similar tools
Deployment:
• Dockerized backend
• Cloud hosting (AWS/GCP)
• DICOM file storage (must be secure and GDPR-compliant)
⸻
Compliance & Ethics:
• All patient data must be anonymized.
• The platform must comply with GDPR (Europe) or HIPAA (USA) requirements for medical data privacy.
⸻
Deliverables:
1. Upload and preview CT scans in a web viewer.
2. AI model trained on provided labeled data (start with 5–10 scans).
3. API to return predictions/segmentations.
4. 3D interactive simulation of implant placement.
5. (Optional) Dashboard to manage patients and results.
⸻
Ideal Candidate:
• Experience with DICOM files and medical imaging
• Background in AI/ML (especially CNNs, segmentation models)
• Frontend skills for visualization and UX
• Familiar with GDPR/HIPAA compliance
⸻
To Apply:
Please include:
• Relevant experience with DICOM or dental/medical imaging.
• Links to similar projects or GitHub repos (if available).
• Estimated timeline for MVP delivery.
• Your suggested tech stack (if different from above).
⸻
Project Overview:
We are building a web-based SaaS platform that uses Artificial Intelligence to analyze dental CT scans (DICOM format) and support implantology diagnosis.
The platform should:
• Allow users (dentists/clinics) to upload DICOM (.dcm) files from dental CT scans.
• Use AI to detect caries, cysts, and available bone volume based on visual patterns (color and location).
• Enable the dentist to simulate dental implant placement in a 3D environment.
• Be trained and validated with the support of a professional implantologist, who will provide labeled data.
This project is in its early stages and will start with an MVP.
⸻
Technical Requirements:
Frontend:
• React.js (preferred)
• Integration with OHIF Viewer or Cornerstone.js for DICOM rendering
• 3D implant simulation (Three.js or similar)
Backend:
• Python + FastAPI or Flask
• File upload system (DICOM)
• API to trigger inference from trained AI model
AI/ML:
• Medical image segmentation using PyTorch or TensorFlow
• Preferred model: nnU-Net or MONAI
• Input: DICOM or preprocessed volume data
• Output: Segmented zones (caries, cysts, bone availability)
Data Format:
• Input: .dcm (DICOM format)
• Annotations: Provided by an implantologist using 3D Slicer or similar tools
Deployment:
• Dockerized backend
• Cloud hosting (AWS/GCP)
• DICOM file storage (must be secure and GDPR-compliant)
⸻
Compliance & Ethics:
• All patient data must be anonymized.
• The platform must comply with GDPR (Europe) or HIPAA (USA) requirements for medical data privacy.
⸻
Deliverables:
1. Upload and preview CT scans in a web viewer.
2. AI model trained on provided labeled data (start with 5–10 scans).
3. API to return predictions/segmentations.
4. 3D interactive simulation of implant placement.
5. (Optional) Dashboard to manage patients and results.
⸻
Ideal Candidate:
• Experience with DICOM files and medical imaging
• Background in AI/ML (especially CNNs, segmentation models)
• Frontend skills for visualization and UX
• Familiar with GDPR/HIPAA compliance
⸻
To Apply:
Please include:
• Relevant experience with DICOM or dental/medical imaging.
• Links to similar projects or GitHub repos (if available).
• Estimated timeline for MVP delivery.
• Your suggested tech stack (if different from above).