Bernhard Kainz (bkainz)

bkainz

Geek Repo

Company:Imperial College London

Location:United Kingdom

Home Page:http://bernhard-kainz.com/

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Bernhard Kainz's repositories

fetalReconstruction

GPU accelerated source code for motion compensation of multi-stack MRI data

ShaderLabFramework

The Shader Lab Framework is a teaching tool to solidify the fundamentals of Computer Graphics with OpenGL 4.0 and GLSL.

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fastreg

fast non-rigid medical image registration via accelerated optimisation on the manifold of diffeomorphisms

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Attention-Gated-Networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

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SonoNet-weights

Model descriptions and weights for all the variations of the SonoNet for real-time fetal standard scan plane detection.

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cnn_depth_tensorflow

depth estimation using tensorflow

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ct_lung_segmentation

docker argo fork

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draw2d_js.app.brainbox

see here http://freegroup.github.io/draw2d_js.app.brainbox

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drop2

drop2 - intensity-based image registration

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FastFlowNet

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation (ICRA 2021)

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gpuview

A lightweight web dashboard for monitoring GPU usage

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lungmask

Automated lung segmentation in CT

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MIRTK

The Medical Image Registration ToolKit (MIRTK), the successor of the IRTK, contains common CMake build configuration files, core libraries, and basic command-line tools. Extension packages are hosted by the MIRTK GitHub group at

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ml-revision

Revision notes for machine learning

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MONAI

AI Toolkit for Healthcare Imaging

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MRIMotionCompensation

GPU accelerated approach to compensate motion from multiple stacks of MRI slices.

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mt_lecture_slides

These are the lecture slides used at FAU Erlangen-Nuremberg, Germany for the lecture "Medical Engineering". This class gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography. Open Access Link to the Text Book: https://link.springer.com/book/10.1007/978-3-319-96520-8#about Link to Video Recordings on YouTube: https://www.youtube.com/watch?v=vvftvjnXzsY&list=PLpOGQvPCDQzsgK1XuhUXO8r9M4WRqhvDf

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multinerf

A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF

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pyro

Deep universal probabilistic programming with Python and PyTorch

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RATCHET

RAdiological Text Captioning for Human Examined Thoraxes

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Raytracer-In-Excel

Raytracer in our favourite spreadsheet application!

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streamlit

Streamlit — The fastest way to build custom ML tools

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temperature_scaling

A simple way to calibrate your neural network.

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tf_unet

Generic U-Net Tensorflow implementation for image segmentation

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warp

Workspace Autonomous Reservation Program - a system to help you efficiently manage hybrid (assigned, hot-desks, etc) office space.

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