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Visualization

Automated detection of focal epilepsy based on brain morphometrics

Focal epilepsy is a type of epilepsy in which seizures originate from a specific region of the brain, often associated with structural abnormalities visible on neuroimaging. Accurate localization of the epileptogenic zone is essential for effective treatment planning, especially in cases considered for surgical intervention. In this project, we aim to classify the anatomical region of seizure onset using structural MRI data (T1-weighted images) processed with FreeSurfer.

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fMRI Stats Exploration

This project aimed to further my intuitive understanding of fMRI data. Around 20 interactive/static figures of various statistics of raw fMRI data, confounds and atlased data were produced. Special efforts have been made to make the analysis highly and easily reproducible.

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Images10K Compendium

A web-based tool for exploring visual datasets across real-world categories using carousels, tables, and interactive views.

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Validating χ-separation using phantom simulations

How can we validate χ-separation algorithm? In the absence of ground truth to validate χ-separation, my project aims to validate the χ-separation results using realistic in-silico head phantom simulations. Simulations offer a valuable advantage by providing a controlled environment where we can define and manipulate various parameters with known ground truth values. By choosing specific values for the simulation, we can create a ground truth against which we can compare the results obtained through the χ-separation algorithm.

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Experimenting with Occlusion methods to visualize the features learned by a CNN from audio or visual inputs

This project has for goal to explore, understand and learn how to create comprehensive visualizations of the features learned by a convolution neural network, whether the model is specialized in auditory or visual input.

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