btcrabb's repositories
Python-Projects-in-Machine-Learning
A collection of machine learning projects, programmed in python and implemented using Jupyter Notebooks
caffe
Caffe fork that supports Conditional Random Fields (CRF) and Weight Maps
CAP-Automated-Pipeline
Fully-automated, deep-learning based pipeline to generate biventricular cardiac models from raw cine SSFP MRI images.
CAP-Automation
A repository containing tools for automating statistical cardiac modeling in association with the Cardiac Atlas Project.
CMRG-ct2mri
Directions and python scripts for generating CIM-compatible DICOM files from CT images for statistical cardiac modeling.
Curriculum-Modeling
In this repository, we will explore the impact of interleaved vs. blocked training schedules on the ability of a multi-task neural network to learn a radiology task. If the neural networks demonstrate results consistent with human learners, it may be possible to simulate curriculum changes and human subject experimentation using machine learning.
NSQIP_ML
A repository to develop predictive algorithms for the NSQIP pituitary tumor dataset