MIC-DKFZ

MIC-DKFZ

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Division of Medical Image Computing, German Cancer Research Center (DKFZ)

Location:Heidelberg, Germany

Home Page:https://www.dkfz.de/en/mic/

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MIC-DKFZ's repositories

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medicaldetectiontoolkit

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

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batchgenerators

A framework for data augmentation for 2D and 3D image classification and segmentation

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nnDetection

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

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trixi

Manage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.

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TractSeg

Automatic White Matter Bundle Segmentation

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HD-BET

MRI brain extraction tool

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basic_unet_example

An example project of how to use a U-Net for segmentation on medical images with PyTorch.

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mood

Repository for the Medical Out-of-Distribution Analysis Challenge.

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MITK-Diffusion

MITK Diffusion - Official part of the Medical Imaging Interaction Toolkit

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RegRCNN

This repository holds the code framework used in the paper Reg R-CNN: Lesion Detection and Grading under Noisy Labels. It is a fork of MIC-DKFZ/medicaldetectiontoolkit with regression capabilites.

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Hyppopy

Hyppopy is a python toolbox for blackbox optimization. It's purpose is to offer a unified and easy to use interface to a collection of solver libraries.

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RTTB

Swiss army knife for radiotherapy analysis

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image_classification

:dart: Deep Learning Framework for Image Classification & Regression in Pytorch for Fast Experiments

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image-time-series

Code for deep learning-based glioma/tumor growth models

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cmdint

CmdInterface enables detailed logging of command line and python experiments in a very lightweight manner (coding wise). It wraps your command line or python function calls in a few lines of python code and logs everything you might need to reproduce the experiment later on or to simply check what you did a couple of years ago.

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gpconvcnp

Code for "GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data"

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generalized_yolov5

An extension of YOLOv5 to non-natural images together with 5-Fold Cross-Validation

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MatchPoint

MatchPoint is a translational image registration framework written in C++. It offers a standardized interface to utilize several registration algorithm resources (like ITK, plastimatch, elastix) easily in a host application.

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