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DeepNeuro
A deep learning python package for neuroimaging data. Made by:qtim_Tutorials
Jupyter notebooks and other tutorials for medical imaging and deep learning, courtesy of the QTIM lab.SiameseChange
qtim_ROP
Code base for preprocessing, segmentation and classification of retinal imagesqtim_tools
A set of tools used for quantitative analysis of and machine learning from 3D medical images. Created by the Quantitative Tumor Imaging Lab at Martinos.Assessing-Saliency-Maps
DeepRad
A deep learning python package for medical imaging data.qtim_PreProcessor
Resources and pipelines used for pre-processing medical imaging data at the Quantitative Tumor Imaging Lab at the Martinos Center (MIT/HST). Includes Docker resources.SlicerSegmentationWizard
This is a 3D model-based segmentation tool for 3D Slicer. It includes utilities for calculating subtraction maps and thresholding intensities. It can be downloaded as an extension to 3D Slicer.PXS-score
TBDbrats2017
Submission for BRATS 2017qtim-lab.github.io
A repository for the public-facing web page of the Quantiative Tumor Imaging Lab at the Martinos Center.FeaturePrediction_ROP
Networks to predict systemic features such as gender and age in ROPdl-prediction-brca-tiph
Implementation of the paper "Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology" by Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett, Katharina V. Hoebel, Mason Cleveland, Syed Rakin Ahmed, Elizabeth Gerstner, Jayashree Kalpathy-Cramer, Jaime S. Cardoso, Christopher P. Bridge and Albert E. Kim.trame_optimeyes
trame tools and visualizationsMedICI
Composite Challenge PlatformAdrenalMGB-Version-1
Preprocessing and neural network code to train an adrenal gland segmenter and classifier using contrast CT abdominal imaging.3D_CNN_Regression
A model for using input 3D volumes for creating scalar output 3D volumesqtim_gbmSegmenter
This is a self-contained Docker container for segmenting high- and low-grade glioblastomas in MR scans using deep learning.qtim_vessels
CU_Project_Template
A template for using the CU environments and tracking generated datadeeprop
A web-based telemedicine platform for retinopathy of prematuritymonaiLabelExploration
Get MonaiLabel server running and establish an input output workflowDeepTofts
Addressing-catastrophic-forgetting-for-medical-domain-expansion
qtim_DCE
A collection of open-source DCE analysis programs in Python, Matlab, and 3D Slicer.Image-Comparator
Updated Image Comparator and ClassifierRetinavsFace_ROP
neurofit
A python library for fitting neuroscience algorithms with deep learning methods.ROP_app
MedSAM
Intro to MedSAM ModelLLM-Report-Labeling
FL_ViT_pretraining
preprocessing
`preprocessing` is a python library designed for the purpose of preprocessing MRI data at QTIM. It currently supports reorganization of dicom and nifti files to follow BIDS conventions, dicom to nifti conversion, and preprocessing for brain data. Its outputs are intended to follow the BIDS organizational scheme.federatedLearning_glaucoma_segmentation
Federated Learning Optic Disc and Cup Segmentation Model for Glaucoma Monitoring in Color Fundus Photographs(CFPs)Love Open Source and this site? Check out how you can help us