.. Localise documentation master file, created by sphinx-quickstart on Sun Oct 8 17:56:04 2023. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to Localise's documentation! ==================================== **LOCALISE** is a Python library for segmentating prevalent surgical targets using multimodal MRI. This toolbox uses Image Quality Transfer techniques to transfer anatomical information from high-quality data to a wide range of connectivity features in low-quality data. The goal is to augment the inference on DBS targets localisation even with compromised data quality. At present, the toolbox supports: - Localising the Vim nucleus of the thalamus, given the T1 and the diffusion MRI data. - Training a model for localising a new target, given the T1 and the diffusion MRI data. Future releases will include: - Localising the STN, ACC, and other targets... .. note:: This project is under active development, and the API might still change substantially at any time! How to Get Started ------------------ 1. If the toolbox is not installed, following the :ref:`Installation Instructions `. 2. If you are not sure what data you need and how to prepare them, check out the :ref:`Prepare Your Data `. 3. If you simply want to localise a target using pre-trained models, check out the :ref:`Predict Mode `. Look through the tutorials. 4. If the toolbox doesn't include the target you want to localise, and you want to train a custom model tailored for your own data, check out the :ref:`Train Mode `. 5. For more information about the toolbox, check out `our paper `_. .. toctree:: :maxdepth: 3 :caption: Contents: sections/installation sections/usage sections/api sections/ref Contributors ============ The original toolbox was written by Ying-Qiu Zheng. Other Contributors: - Saad Jbabdi