Slicer Automated Dental Tools

The Slicer Automated Dental Tools extension provides automatic dental and craniofacial analysis capabilities. It features a user-friendly graphical interface on 3D Slicer, enabling users to perform complex tasks without any coding expertise.

<p align="center"> <img src="SlicerAutomaticTools.png" alt="Extension Logo" width="200"/> </p>

Compatible with both stable and nightly versions of 3D Slicer. Latest versions supported: 5.7.0 (nightly) and 5.6.1 (stable)

Overview

Slicer automated dental tools is an extension that allows users to perform automatic segmentation, landmark identification and Automatic Orientation on CBCT scans and Intra Oral Scan (IOS) using machine learning tools where the learning mdoels are continously updated.

<p align="center"> <img src="ADT-exemple.png" alt="Exemples"/> </p>

Features

• Simple: Perform time consuming task with a few clicks.
• Automatic: Automate important Dental and Cranio Facial analysis tasks.
• Flexible: The user can choose which models to use to perform the automated task. New models can be added easily.

Modules

| Name | Description | |------|-------------| | AMASSS | Perform automatic segmentation of CBCT scan. AMASSS is an acronym for Automatic Multi-Anatomical Skull Structure Segmentation. | | ALI | Perform automatic landmark identification on either CBCT or IOS scans. ALI is an acronym for Automatic Landmark Identification. | | ASO | Perform automatic orientation either on IOS or CBCT files. | | AReg | Perform automatic registration on IOS or CBCT files. | | AutoCrop3D | Automatically crop a folder of CBCT scans with the same region of interest. | | AutoMatrix| Automatically apply one or different matrix to a folder of IOS or CBCT scans. | | MedX | Summarize clinical notes and generate a comprehensive comorbidity dashboard. | | Medical Data Anonymizer | Automatically anonymize sensitive information in medical documents (DOCX, PDF, TXT, CSV, XML, ODT). | | MRI2CBCT | Contains the steps to perform the registration of MRI and CBCT scans.| | FlexReg | Registration of IOS patient per patient with customizable patch creation. | | DOCShapeAXI | Automatic classification of 3D Shape. DOC-ShapeAXI is an acronym for Dental Oral and Craniofacial Shape Analysis eXplainability and Interpretability. | | BatchDentalSegmentator | DentalSegmentator in batch for mixed or permanent dentition | | CLI-C |Classification and Localization of Impacted Canines |

These modules provide a convenient user interface, are available through the Automated Dental Tools module category, and share common features :

Input

• All modules can work with one file or a whole sample (folder) as input.
• If the input is a single file already loaded, the result of the predicton will directly show up on the slice views.

Output

• By selecting the "Group output in a folder" checkbox, all the ouput files will be grouped in a single folder for each patient.
• All modules allows the user to save the output in the input folder, or by unchecking the "Save prediction in scan folder" the user can choose a custom output folder.
• The "Prediction ID" field is for the user to choose what will appear on the output file name. ("Pred" by default)

Additionally, the following modules are implemented as python scripted command-line (CLI) modules available in the Automated Dental Tools.Advanced module category and are used internally by the modules described above.

| Name | Description | |------|-------------| | AMASSS_CLI | Perform automatic segmentation of CBCT scans | | ALI-CBCT | Perform automatic landmark identification of CBCT scans| | ALI-IOS | Perform automatic landmark identification of IOS scans| | ASO-CBCT | Perform automatic orientation of CBCT scans | | ASO-IOS | Perform automatic orientation of IOS scans | | AReg-CBCT | Perform automatic registration of CBCT scans | | AReg-IOS | Perform automatic registration of IOS scans | | AutoMatrix-CLI | Apply transformation matrices to input volumes or landmarks | | MedX-Dashboard | CCreate a visual dashboard from structured comorbidity summaries | | MedX-Summarize | Extract TMJ-related comorbidities from unstructured clinical notes using a fine-tuned LLM | | Medical Data Anonymizer | Automatically anonymized text files. | | MRI2CBCT_APPROX | Perform automatic approximation of an MRI to a CBCT | | MRI2CBCT_LR_CROP | Separate volumes into left and right halves for bilateral analysis | | MRI2CBCT_ORIENT_CENTER_MRI | Perform orientation and centering of MRI scans | | MRI2CBCT_RESAMPLE_CBCT_MRI | Perform resample of MRI and CBCT scans | | MRI2CBCT_REG | Perform registration of MRI-CBCT scans | | MRI2CBCT_TMJ_CROP | Automatically crop the TMJ region from CBCT, segmentations, or MRI | | FlexReg_CLI | Perform creation of patch and registration on IOS scans. | | DOCShapeAXI | Perform automatic classification of 3D Shape. | | BatchDentalSegmentator | DentalSegmentator in batch for mixed or permanent dentition | | CLI-C |Classification and Localization of Impacted Canines |

Requirements

• In addition of the Slicer System requirements, for best performance, 12GB of memory is recommended.
• :warning: Trained networks are required to be manually downloaded. See requirements section specific to each module.

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AMASSS Module

<img src="AMASSS/Resources/Icons/AMASSS.png" alt="Extension Logo" width="50"/>

AMASSS module will allow you to segment CBCT scan using AMASSS algortihm.

Prerequisites

• Download the trained models for AMASSS using the Download latest models button in the module Input section.

Module structure

Input file: The input has to be an oriented CBCT. It can be a single CBCT scan loaded on slicer or a folder containg CBCTs with the following extention:

.nrrd / .nrrd.gz
.nii  / .nii.gz
.gipl / .gipl.gz

Available sample data for testing: MG_test_scan.nii.gz

Load models: The user has to indicate the path of the folder containing the trained models for AMASSS.

Segmentation selection: The user can choose the structure to segment using the selection table. Depending on the type of CBCT to segment, the user can select the "Use small FOV models" checkbox to use on higher definition scans.

Output option: By selecting the "Generate surface files" checkbox. The user will also get a surface model of the segmentation that will be saved in a "VTK files" folder and will be automatically loaded in slicer at the end of the prediction if working on a single file.

Advanced option:

• You can increase/decrease the precision of the segmentation (going above 50 will drastically increase the prediction time and is not necesary worth it, going under 50 will make the prediction much faster but less accurate)
• If the user whant to generate surface files, he can choose the smothness applied on the model.
• Depending on your computer power, you can increase the CPU and GPU usage to increase the predictio speed.

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ALI Module

<img src="ALI/Resources/Icons/ALI.png" alt="Extension Logo" width="50"/>

ALI module provide a convenient user interface allowing to identify landmarks on different type of scans:

• CBCT scan
• IOS scan

ALI-CBCT

The implementation is based on the ALI-CBCT algortihm originally developed by Maxime Gillot at https://github.com/Maxlo24/ALI_CBCT.

Prerequisites

• Download the trained models for ALI-CBCT using the Download latest models button in the module Input section.

Module structure

Input file: The input has to be an oriented CBCT. It can be a single CBCT scan loaded on slicer or a folder containg CBCTs with the following extention:

.nrrd / .nrrd.gz
.nii  / .nii.gz
.gipl / .gipl.gz

Available sample data for testing: MG_test_scan.nii.gz

Load models: The user has to indicate the path of the folder containing the trained models for ALI-CBCT.

Landmark selection: Once the folder containing the trained models is loaded. The user can choose the landmark he want to identify with the table showing the available landmarks:

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ALI-IOS

The implementation is based on the ALI-IOS algortihm originally developed by Baptiste Baquero at https://github.com/baptistebaquero/ALIDDM.

Prerequisites

• Download the [trained models for ALI-IOS](https://github.com/baptistebaquero/ALIDDM/releases/tag/v1.0.3