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Automatic Measurement of the Root Canal Working Length — AI & Machine Learning project by YenkoDev

Automatic Measurement of the Root Canal Working Length

Software as a Service

No

Category

AI & Machine Learning

Clients

Confidential

Techstack

PythonPyTorchPyTorch LightningPyQt5OpenCVRaspberry PiFlaskscikit-image

Purpose

This thesis aimed to automate a critical step in endodontic treatment: measuring the root canal working length from periapical X-ray images, replacing manual estimation with a repeatable AI-assisted measurement.

Description

A PyQt5 desktop application segments root canals from periapical radiographs using a U-Net model built with segmentation_models_pytorch and trained in PyTorch Lightning. Captured X-ray film is digitized by a Raspberry Pi camera rig served over a Flask API, then preprocessed with cropping and CLAHE contrast enhancement. From each predicted mask, a medial-axis skeleton and graph-based path analysis trace the canal and convert its pixel length to millimeters, with results and annotated images saved per patient.

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