Curved Projection Reformation

Overview

Description

Assuming that we already know the image of the centerline, we want the lumen to be displayed on a plane, which requires curved projection reformation(CPR).The figure below is a common coronary centerline display in the paper.

Function introduction

The center line is a representation of a series of points.

You can call the function cpr(img_name, center_line_name) directly, where img_name represents the path of the image and center_line_name represents the path of the centerline point. The former supports .nii.gz and .mha files. The latter only supports .npy files.

The center line is represented by a 3D image.

You need to first convert the centerline image into a series of sequential points. Here provides a minimum path method for continuous centerline extraction, which is called find_point_list(thin_label_name, start, end), where thin_label_name is the path of 3D image, start is the coordinates of the starting point of the center line and end is the coordinates of the ending point of the center line.This function will save the center line as an .npy file.

Owner
夜听残荷
夜听残荷
LSTM-VAE Implementation and Relevant Evaluations

LSTM-VAE Implementation and Relevant Evaluations Before using any file in this repository, please create two directories under the root directory name

Lan Zhang 5 Oct 08, 2022
Recovering Brain Structure Network Using Functional Connectivity

Recovering-Brain-Structure-Network-Using-Functional-Connectivity Framework: Papers: This repository provides a PyTorch implementation of the models ad

5 Nov 30, 2022
C3D is a modified version of BVLC caffe to support 3D ConvNets.

C3D C3D is a modified version of BVLC caffe to support 3D convolution and pooling. The main supporting features include: Training or fine-tuning 3D Co

Meta Archive 1.1k Nov 14, 2022
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers

DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (

Jaemin Cho 98 Dec 15, 2022
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021]

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

Automation and Intelligence for Civil Engineering (AI4CE) Lab @ NYU 98 Dec 21, 2022
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.

Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition This is the research repository for Vid2

Future Interfaces Group (CMU) 26 Dec 24, 2022
Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner

Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges

Andrew Stolman 1 Apr 30, 2021
Python scripts to detect faces in Python with the BlazeFace Tensorflow Lite models

Python scripts to detect faces using Python with the BlazeFace Tensorflow Lite models. Tested on Windows 10, Tensorflow 2.4.0 (Python 3.8).

Ibai Gorordo 46 Nov 17, 2022
Subgraph Based Learning of Contextual Embedding

SLiCE Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks Dataset details: We use four public benchmark da

Pacific Northwest National Laboratory 27 Dec 01, 2022
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space

Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte

38 Dec 15, 2022
SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling

SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling Reference Main paper to be cited (Di Wu et al., 2020) @article

Moore 34 Nov 03, 2022
Interactive Image Segmentation via Backpropagating Refinement Scheme

Won-Dong Jang and Chang-Su Kim, Interactive Image Segmentation via Backpropagating Refinement Scheme, CVPR 2019

Won-Dong Jang 85 Sep 15, 2022
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification

Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv

陈志豪 8 Oct 13, 2022
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the o

1 Jan 04, 2022
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning

FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cr

Scaleout 75 Nov 09, 2022
Official Implementation of "Third Time's the Charm? Image and Video Editing with StyleGAN3" https://arxiv.org/abs/2201.13433

Third Time's the Charm? Image and Video Editing with StyleGAN3 Yuval Alaluf*, Or Patashnik*, Zongze Wu, Asif Zamir, Eli Shechtman, Dani Lischinski, Da

531 Dec 20, 2022
Using Python to Play Cyberpunk 2077

CyberPython 2077 Using Python to Play Cyberpunk 2077 This repo will contain code from the Cyberpython 2077 video series on Youtube (youtube.

Harrison 118 Oct 18, 2022
A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets

HOW TO USE THIS PROJECT A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets Based on DeepLabCut toolbox, we run wit

1 Jan 10, 2022
LoL Runes Recommender With Python

LoL-Runes-Recommender Para ejecutar la aplicación se debe llamar a execute_app.p

Sebastián Salinas 1 Jan 10, 2022
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap

Cameron Davidson-Pilon 25.1k Jan 02, 2023