Which 3D Spine Recontruction written (pre-requisite) in Python ?

Jean-Marc Valiadis You're right to consider the impact of surrounding structures like ribs, sternum, and pelvis, as well as age-related changes like osteophytes.

Preprocessing the CT Images: Your first step should be preprocessing the CT images. This involves enhancing the images for better contrast between the vertebrae and the surrounding tissues. Techniques like histogram equalization and adaptive thresholding can be very helpful here.

Segmentation of Vertebrae: The heart of your project lies in accurately segmenting the vertebrae. Given the complexity of the spinal region, traditional segmentation methods might not suffice. You might want to explore advanced machine learning techniques, particularly deep learning models. Convolutional Neural Networks (CNNs) have shown remarkable results in medical image analysis. Training a CNN to recognize and segment the vertebrae would be pivotal. You'll need a substantial dataset of annotated CT images for training and validation.

Identifying Anterior Bodies and Plane Orientations: Once you have segmented the vertebrae, identifying the anterior bodies and their superior and inferior planes would be the next step. This can be challenging, especially considering the variability in spine anatomy and the presence of artefacts. Developing algorithms that can compute the orientation of each vertebral body relative to its neighbors would be crucial.

Handling Artefacts and Age-Related Changes: Artefacts from ribs, sternum, and pelvis, as well as changes due to aging like osteophytes, can complicate the analysis. This is where robust image processing and pattern recognition algorithms come into play. You might need to incorporate techniques that specifically detect and account for these artefacts and changes.

Python Libraries and Tools: In Python, libraries like NumPy, Pandas, and Matplotlib are fundamental for data handling and visualization. For image processing, OpenCV and scikit-image offer extensive functionalities. For deep learning, TensorFlow and Keras are widely used and have strong community support.

Testing and Validation: Rigorous testing and validation on diverse datasets are crucial. This ensures that your tool is reliable across different age groups, body types, and medical conditions.

Remember, Each patient's anatomy is unique, and so are the challenges in imaging and interpretation. Stay patient and persistent. The satisfaction of contributing to the medical field with a tool that aids in better diagnosis and treatment is truly unparalleled.

What are some underexplored theories and concepts in Activated Carbon as A Water Filter?

What are some underexplored theories and concepts in Activated Carbon as A Water Filter?

What properties of water shall be analyzed and evaluated to test the effectiveness of activated carbon?

Who are the possible experts I can reach out to regarding the reseach topic: Activated Carbon as Water Filter?

How can we measure the reliability and validity of our survey questionnaire?

Best loss function for special classification problem in neural networks ?

Anybody to help me with Code source for DOUBLE CONCAVE FRICTION PENDULUM BEARINGS Please?

Are normality checks required for large sample sizes?

How to design a reactive extraction process in Aspen Plus?

Could speech recognition software be developed that DOESN'T convert sounds into waveforms? If not, what does it say about the semiotics of knowledge?

How to repeat an operation on an atom selection for multiple times in PyMol?

How to define and get results (stresses) for certain points of a model in abaqus, using python? When the size of the model changes?

Which is suitable for use with Python? MySQL or SQL Server?

Can anyone provide the Support vector regression code structure of LIBSVM MATLAB or python ?

How to modify Johnson cook equation in ABAQUS?

How can we limit artifacts caused by rotation in fiber photometry?

No module named 'tensorflow.keras.backend.tensorflow_backend' ?

Implementation of chance-constrained optimization problem via scenario approach?

Bayesian decision trees and bayesian regression trees in Python and/or R?

Are there packages (R or Python) for simple models (bucket?) to assess soil water content?