Description
Materialise Mimics Innovation Suite v21 is a medical image processing software used for segmenting medical images to create 3D models of patient anatomy. It enables users to visualize, analyze, and edit these models for applications like virtual surgical planning, device design, and 3D printing for medical applications. Key features include image-based segmentation, anatomical analysis, treatment and surgical planning tools, and integration with other design and FEA software
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Import and visualize:
Imports medical images from various formats, including DICOM, and displays them in multiple views (coronal, axial, sagittal) alongside 3D models.
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Segmentation:
Creates highly accurate 3D models of patient anatomy from medical scans using semi-automatic and AI-powered tools to segment specific anatomical regions
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Analysis and measurement:
Provides tools for analyzing anatomy, performing measurements on images and 3D models, and identifying anatomical landmarks.
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3D model editing:
Allows for editing and refining the 3D models, and can link to third-party software for further design work, such as with the 3-matic design software.
Applications and workflow
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Virtual planning:
Enables virtual surgical planning, including planning cuts, placing implants, and simulating procedures on the 3D model.
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3D printing:
Facilitates the creation of output files for additive manufacturing (3D printing) of anatomical models, surgical guides, and patient-specific implants.
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Data export:
Exports segmented images, measurements, and 3D models to third-party software packages like CAD and Finite Element Analysis (FEA) programs.
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Automation:
Uses Python scripting to automate repetitive tasks and streamline workflows.
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Medical device development:
Helps medical device companies reduce design iterations, speed up time-to-market, and improve device fit through virtual patient models.
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Clinical applications:
Supports personalized medicine in areas like orthopaedics, cranio-maxillofacial surgery, and cardiovascular applications.
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Research and education:
Used by researchers to address anatomical engineering challenges and educate the next generation of innovators.
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