U-Net for GBM

Overview

My Final Year Project(FYP) In National University of Singapore(NUS)

You need

Pytorch(stable 1.9.1) 

Both cuda version and cpu version are OK

File Structure

📦FYP-U-Net
 ┣ 📂data
 ┃ ┣ 📂imgs
 ┃ ┃ ┣ 📌···.tif
 ┃ ┃ ┗ ···
 ┃ ┣ 📂masks
 ┃ ┃ ┣ 📌···_mask.tif
 ┃ ┃ ┗ ···
 ┃ ┣ 📂PredictImage 
 ┃ ┃ ┣ 📌0.tif
 ┃ ┃ ┣ 📌1.tif
 ┃ ┃ ┗ ···
 ┃ ┣ 📂SaveImage
 ┃ ┃ ┣ 📌0.tif
 ┃ ┃ ┣ 📌1.tif
 ┃ ┃ ┗ ···
 ┃ ┗ 📂Source
 ┃ ┃ ┣ 📂TCGA_CS_4941_19960909
 ┃ ┃ ┃ ┣ 📌TCGA_CS_4941_19960909_1.tif
 ┃ ┃ ┃ ┣ 📌TCGA_CS_4941_19960909_1_mask.tif 
 ┃ ┃ ┃ ┣ 📌TCGA_CS_4941_19960909_2.tif
 ┃ ┃ ┃ ┣ 📌TCGA_CS_4941_19960909_2_mask.tif 
 ┃ ┃ ┃ ┗ ···
 ┃ ┃ ┣ 📂TCGA_CS_4942_19970222
 ┃ ┃ ┗ ···
 ┣ 📂params
 ┃ ┗ 📜unet.pth
 ┣ 📓README,md
 ┣ 📄data.py
 ┣ 📄net.py
 ┣ 📄utils.py
 ┗ 📄train.py
  • 'data' dir contains the origin dataset in 'Source' dir. And the dataset can be download in Kaggle (https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/). And also you can use different dataset.
  • 'imgs' contains images and 'masks' contains corresponding masks to images. Corresponding masks have a _mask suffix. More inforamtion you can check in kaggle.
  • 'SaveImage' is meant for store train results and 'PredictImage' is meant for store test results.
  • 'params' is meant for store model.

Quick Up

Run train.py

Change DataSet

  • Delte all images in data dir and its subdir.

  • Install dataset from kaggle or anything you like(PS. Corresponding masks must have a _mask suffix) into 'Source' dir

  • Run data.py

    python3 data.py
    

    Remember change the path. After this, you will get images and masks in imgs dir and masks dir.

  • Run train.py

    python3 train.py
    

    Remember change the path. And you can see the results in 'SaveImage' dir and 'PredictImage' dir.

Results

Segment Image

Pre-trained model

https://drive.google.com/file/d/1yyrITv7BQf9kDnP__g6Qa3_wUPD1c_i_/view?usp=sharing

Owner
PinkR1ver
Artist, go with the flow, stay up late
PinkR1ver
Deep Markov Factor Analysis (NeurIPS2021)

Deep Markov Factor Analysis (DMFA) Codes and experiments for deep Markov factor analysis (DMFA) model accepted for publication at NeurIPS2021: A. Farn

Sarah Ostadabbas 2 Dec 16, 2022
Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation

Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation Woncheol Shin1, Gyubok Lee1, Jiyoung Lee1, Joonseok Lee2,3, Edward Ch

Woncheol Shin 7 Sep 26, 2022
Minimal diffusion models - Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)

Minimal code and simple experiments to play with Denoising Diffusion Probabilist

Rithesh Kumar 16 Oct 06, 2022
State-of-the-art language models can match human performance on many tasks

Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p

OpenAI 259 Jan 08, 2023
QuadTree Attention for Vision Transformers (ICLR2022)

This repository contains codes for quadtree attention. This repo contains codes for feature matching, image classficiation, object detection and seman

tangshitao 222 Dec 28, 2022
The code for paper "Learning Implicit Fields for Generative Shape Modeling".

implicit-decoder The tensorflow code for paper "Learning Implicit Fields for Generative Shape Modeling", Zhiqin Chen, Hao (Richard) Zhang. Project pag

Zhiqin Chen 353 Dec 30, 2022
ML for NLP and Computer Vision.

Sparrow is our open-source ML product. It runs on Skipper MLOps infrastructure.

Katana ML 2 Nov 28, 2021
Oriented Object Detection: Oriented RepPoints + Swin Transformer/ReResNet

Oriented RepPoints for Aerial Object Detection The code for the implementation of “Oriented RepPoints + Swin Transformer/ReResNet”. Introduction Based

96 Dec 13, 2022
Thermal Control of Laser Powder Bed Fusion using Deep Reinforcement Learning

This repository is the implementation of the paper "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", linked here. The project makes use of the Deep Reinforcement Library

BaratiLab 11 Dec 27, 2022
PyElecCL - Electron Monte Carlo Second Checks

PyElecCL Python program to perform second checks for electron Monte Carlo radiat

Reese Haywood 3 Feb 22, 2022
Transformer part of 12th place solution in Riiid! Answer Correctness Prediction

kaggle_riiid Transformer part of 12th place solution in Riiid! Answer Correctness Prediction. Please see here for more information. Execution You need

Sakami Kosuke 2 Apr 23, 2022
Differentiable Simulation of Soft Multi-body Systems

Differentiable Simulation of Soft Multi-body Systems Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin [Paper] [Code] Updates The C++ backend s

YilingQiao 26 Dec 23, 2022
Official Matlab Implementation for "Tiny Obstacle Discovery by Occlusion-aware Multilayer Regression", TIP 2020

Tiny Obstacle Discovery by Occlusion-aware Multilayer Regression Official Matlab Implementation for "Tiny Obstacle Discovery by Occlusion-aware Multil

Xuefeng 5 Jan 15, 2022
Neural Nano-Optics for High-quality Thin Lens Imaging

Neural Nano-Optics for High-quality Thin Lens Imaging Project Page | Paper | Data Ethan Tseng, Shane Colburn, James Whitehead, Luocheng Huang, Seung-H

Ethan Tseng 39 Dec 05, 2022
Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment This repository shows two tasks: Face landmark detection and Fac

BoomStar 51 Dec 13, 2022
Source code for our paper "Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures"

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Code for the Multiplex Molecular Graph Neural Network (M

shzhang 59 Dec 10, 2022
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

Benedek Rozemberczki 188 Dec 29, 2022
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models

Finding an Unsupervised Image Segmenter in each of your Deep Generative Models Description Recent research has shown that numerous human-interpretable

Luke Melas-Kyriazi 61 Oct 17, 2022
A scikit-learn-compatible module for estimating prediction intervals.

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

SimAI 584 Dec 27, 2022
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021]

Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021] Abstract Analyzing complex scenes with DNN is a challenging ta

Irene Yuan 24 Jun 27, 2022