AKA Math's repositories
PortPy
Opensource radiation treatment planning system in Python
open-kbp
Develop dose prediction models for knowledge-based planning in radiotherapy
MIALab
Medical Image Analysis Lab (MIALab), University of Bern
amithjkamath.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
doselo
DOSELO (Dose Segmentation Loss Function): Dose Guidance for Radiotherapy-oriented Deep Learning Segmentation
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
deepdosesens
How Sensitive Are Deep Learning Based Radiotherapy Dose Prediction Models To Variability In Organs At Risk Segmentation?
stochastic_segmentation_networks
Stochastic Segmentation Networks
context_vs_fbr
This repository supports our recent MedNeurIPS 2022 abstract on the importance of context versus foreground-to-background ratio in segmentation tasks.
shifts
This repository contains data readers and examples for the three tracks of the Shifts Dataset and the Shifts Challenge.
template-matching
This is a simple streamlit + OpenCV demonstration of template matching.
image-registration
This is a demonstration of how transformation matrices affect registration for the rigid case.
montyhall
This is an interactive Monty Hall problem demonstration with a MATLAB UI.
bme-labs
Repository for materials related to the biomedical engineering lab
codesamples
general code samples in C++, python and MATLAB.
MONAIBootcamp2021
Materials for the 2021 MONAI Bootcamp
PHiSeg-code
Tensorflow Code for "PHiSeg: Capturing Uncertainty in Medical Image Segmentation", Proc. MICCAI 2019
surface-distance
Library to compute surface distance based performance metrics for segmentation tasks.
gpssi
Implementation of the GPSSI paper
CSAODFcode
MATLAB implementation of the CSA ODF Algorithm. More at: http://conservancy.umn.edu/handle/11299/140183
dipy
DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
fastbook
The fastai book, published as Jupyter Notebooks
3DUnetCNN
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation