Solutions to Elliptic and Parabolic Problems via Finite Difference Based Unsupervised Small Linear Convolutional Neural Networks

1 code implementation • 1 Nov 2023 • Adrian Celaya, Keegan Kirk, David Fuentes, Beatrice Riviere

In recent years, there has been a growing interest in leveraging deep learning and neural networks to address scientific problems, particularly in solving partial differential equations (PDEs).

FMG-Net and W-Net: Multigrid Inspired Deep Learning Architectures For Medical Imaging Segmentation

1 code implementation • 5 Apr 2023 • Adrian Celaya, Beatrice Riviere, David Fuentes

Accurate medical imaging segmentation is critical for precise and effective medical interventions.

Brain Tumor Segmentation Image Segmentation +2

A Generalized Surface Loss for Reducing the Hausdorff Distance in Medical Imaging Segmentation

1 code implementation • 8 Feb 2023 • Adrian Celaya, Beatrice Riviere, David Fuentes

Within medical imaging segmentation, the Dice coefficient and Hausdorff-based metrics are standard measures of success for deep learning models.

Image Segmentation Medical Image Segmentation +2

PocketNet: A Smaller Neural Network for Medical Image Analysis

2 code implementations • 21 Apr 2021 • Adrian Celaya, Jonas A. Actor, Rajarajeswari Muthusivarajan, Evan Gates, Caroline Chung, Dawid Schellingerhout, Beatrice Riviere, David Fuentes

Medical imaging deep learning models are often large and complex, requiring specialized hardware to train and evaluate these models.

Medical Image Segmentation Semantic Segmentation