GitHub - RiccardoBiondi/FemurSegmentation
The snalemake pipeline allows you to split a lower limb CT scan into right and left legs and perform an automated femur segmentation in a multi-subject segmentation framework. All the …
ShapeWorks/Examples/Python/femur_cut.py at master - GitHub
The femur data set is comprised of segmented meshes of femurs and corresponding CT
GitHub - eDIMESLab/3DFemurSegmentation
Make sure to add ~/3DFemurSegmentation/lib/ to your Python library path before running. On Ubuntu OS, type:
python - How to segment femur from x-ray in …
2021年5月20日 · In these images take the most prominent feature of the femur bone, say the ball joint, and do a template matching using it on scaled down versions of images. You can do that on a segmented image or on the original …
Femur CT Dataset - PhDthesis
Femur CT Dataset. The training of a deep Neural Network model as the U-Net one requires a large set of image with corresponding labels. We developed some experiments on automatic …
material properties of the femur, but also to investigate the realistic wide range of possible boundary conditions acting on the femur during a fall.
Femur: Shape Model from Meshes with Cutting Planes - GitHub …
Femur: Shape Model from Meshes with Cutting Planes What is the Use Case? The femur use case demonstrates using the shape modeling workflow on a real-world femur dataset. The …
Femur: Group Difference Statistics in Python - ShapeWorks
This use case analyzes the femur shape model obtained from running the Femur: SSM from Meshes with Cutting Planes use case. The data has 21 examples of normal femurs and 5 …
Femur SSM Directly from Images - ShapeWorks
Femur Shape Model Directly from Images What is the Use Case? The deep_ssm use case demonstrates how to get shape models from unsegmented images using deep learning on the femur data. This includes performing data …
fahimehazari/mimics_3matic_Python_scripting - GitHub
Python scripts for mimics and 3-matic to generate volume mesh of implanted model from human femurs and assign linear/non-linear gray scale-based material properties.
