aecelaya

MIST

MIST: A simple, scalable, and end-to-end framework for 3D medical imaging segmentation.

pocketnet

Code for "PocketNet: A Smaller Neural Network for Medical Image Analysis."

gen-surf-loss

Code for implementing and comparing the Generalized Surface Loss to other loss functions

mg-nets

Code for FMG-Net and W-Net architectures

ml-gravity-inversion

Implementation details for networks used in paper "Inversion of Time-Lapse Surface Gravity Data for Detection of 3D CO2 Plumes via Deep Learning."

aecelaya.github.io

My personal website

brats-seg

BraTS-Toolkit

Brats Toolkit: 1. BraTS preprocessor 2. BraTS Segmentor 3. BraTS Fusionator

BraTS-Toolkit-Source

DeepLearningExamples

Deep Learning Examples

docker-images

Dockerfiles for medical imaging containers

euclidean-distance-transform-3d

Euclidean distance transform for multi-label 3D anisotropic images using marching parabolas.

pde-nets

Deep learning approaches to PDEs

julia-dg

Code from CAAM 542 Spring 2023

mist-docs

Read the Docs page for Medical Imaging Segmentation Toolkit (MIST)

mist-tf

TensorFlow version of Medical Imaging Segmentation Toolkit (MIST)

monstr-1.2.1

Slightly modified MONSTR skull-stripping scripts to run on Docker image.

MRDQED

A Magnetic Resonance Data Quality Evaluation Dashboard

neurodocker

Generate custom Docker and Singularity images, and minimize existing containers

Pocket-nnUNet

sqgn

Neural network training with a stochastic quasi-Gauss-Newton method

test-research-website

Testing new template for my personal research page

unet

U-Net Biomedical Image Segmentation