- DL & ML papers for Biology
- DL Papers : Super Resolution
- DL Papers : Segmentation
- Web Review
- DL tool for Biology
- Competition
- DL Model in General
- ML seminar
- Deep learning in R, Selected
- Deep learning in R
- 3D visualization in R
- 3D Deep learning & 3D visualization in Python
- Datasets Summary
- Image Annotation
- Image Processing Packages in R
- Random Forest Segmentation for Bioimages
- javadoc.imagej.net
- Japanese 国際学会 速報
- Japanese
- Machine learning for Bioimage Pose Estimation Wiki
DL & ML papers for Biology
- Martin Schorb et al, Software tools for automated transmission electron microscopy
- Roger Brent et al, Deep learning to predict microscope images, Nature Methods, volume 15, pages868–870 (2018)
- Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
- A guide to deep learning in healthcare
- CDeep3M—Plug-and-Play cloud-based deep learning for image segmentation
- Kohki Konishi et al, Practical method of cell segmentation in electron microscope image stack using deep convolutional neural network
- Varun Gulshan et al, Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
- Yun Liu et al, Artificial Intelligence–Based Breast Cancer Nodal Metastasis Detection
- Diego Ardila et al, End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
- QuPath: Open source software for digital pathology image analysis
- Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multisite study
- Capturing global spatial context for accurate cell classification in skin cancer histology
- Attention U-Net: Learning Where to Look for the Pancreas
- Mattias P. Heinrich et al, Residual U-Net Convolutional Neural Network Architecture for Low-Dose CT Denoising
- Md Zahangir Alom et al, Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
- Kun Zhang et al, Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model
DL Papers : Super Resolution
- Michał Januszewski et al: Segmentation-Enhanced CycleGAN
- Peter H. Li et al. Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment. Microscopy and Microanalysis
DL Papers : Segmentation
- U-Net: Convolutional Networks for Biomedical Image Segmentation
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- Fully Convolutional Networks for Semantic Segmentation
- Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
- H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
- The Importance of Skip Connections in Biomedical Image Segmentation
- Rethinking Atrous Convolution for Semantic Image Segmentation
- Road Extraction by Deep Residual U-Net
- Dongyoon Han et al, Deep Pyramidal Residual Networks
- Sergey Zagoruyko et al, Wide Residual Networks
- M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Real-World Applications
- DUNet: A deformable network for retinal vessel segmentation
- Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions
- terryum/awesome-deep-learning-papers
- Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
- AUTOMATED PULMONARY NODULE DETECTION USING 3D DEEP CONVOLUTIONAL NEURAL NETWORKS
- Hongyang Li et al, Neural Network Encapsulation
- Giuseppe Siracusano et al, In-network Neural Networks
- Using the U-net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images
- Foivos I. Diakogiannis et al, ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data
- J. Caldeira et al, DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks
- Ozan Oktay et al, Attention U-Net: Learning Where to Look for the Pancreas, Computer Vision and Pattern Recognition
Web Review
- Review: U-Net+ResNet — The Importance of Long & Short Skip Connections (Biomedical Image Segmentation)
- Review: U-Net (Biomedical Image Segmentation)
- Review: timzhang642/3D-Machine-Learning
- Review: tangzhenyu/SemanticSegmentation_DL
DL tool for Biology
Competition
DL Model in General
- mrgloom/awesome-semantic-segmentation
- Unet, FPN, Linknet, PSPNet
- MrGiovanni/UNetPlusPlus
- qubvel/segmentation_models
- ykamikawa/tf-keras-PSPNet
- davidtvs/Keras-LinkNet
- shelhamer/fcn.berkeleyvision.org
- Evaluating image segmentation models.
- Grid Search vs Random Search
- A Comprehensive List of Hyperparameter Optimization & Tuning Solutions
- eriklindernoren/Keras-GAN
ML seminar
Deep learning in R, Selected
Deep learning in R
- keras/vignettes/examples/unet_linux.R
- unet with Keras and R
- Guide to Keras Basics
- Keras Examples
- It's that easy! Image classification with keras in roughly 100 lines of code.
- Example of Deep Learning With R and Keras
- mlr-org/mlr
- Hands-On Machine Learning with R
- dlab-berkeley/Unsupervised-Learning-in-R
- dlab-berkeley/Deep-Learning-in-R
- jjallaire/deep-learning-with-r-notebooks
3D visualization in R
3D Deep learning & 3D visualization in Python
Datasets Summary
- arXivTimes/datasets
- awesome-semantic-segmentation#datasets
- Who is the best at X ?
- Kaggle/Biology
- 18 Free Life Sciences, Healthcare and Medical Datasets for Machine Learning
- A survey on Deep Learning Advances on Different 3D Data Representations
Image Annotation
Image Processing Packages in R
- Introduction to EBImage
- The magick package: Advanced Image-Processing in R
- magick.r
- magick vignette
- imager: an R package for image processing
- ROpenCVLite
- ropensci/opencv
- Getting started with imager
- Morphological operations in imager
- Grow/Shrink A Pixel Set
Random Forest Segmentation for Bioimages
- Random Forest for Membrane Detection (by Verena Kaynig)
- Trainable Weka Segmentation in Fiji (by Ignacio Arganda-Carreras, Albert Cardona, Verena Kaynig, Johannes Schindelin)
- Scripting the Trainable Segmentation
javadoc.imagej.net
Japanese 国際学会 速報
Japanese
- TensorFlow 2.X の使い方を VGG16／ResNet50 の実装と共に解説
- ResNetまわりの論文まとめ
- RFtutorial SSII2013
- U-NetでPascal VOC 2012の画像をSemantic Segmentationする
- ディープラーニングにおけるセマンティックセグメンテーションのガイド2017年版
- メディカルAI専門コース オンライン講義資料 5. 実践編: MRI画像のセグメンテーション
- Rでコンピュータービジョン
- cvpaper.challenge in CVPR2015 (PRMU2015年12月)
- MathWorks セマンティック・セグメンテーションの基礎
- Semantic segmentation
- 学習画像/動画作成用アノテーションツールを調べてみた
- U-net構造で、画像セグメンテーションしてみた。（２）
- U-Net：セグメンテーションに特化したネットワーク
- いまさら聞けない機械学習の評価関数
- 今さら聞けない！GitHubの使い方【超初心者向け】
- 今さら聞けないディープラーニングの基本、機械学習とは何が違うのか
- .1 Git の基本
- 基本的なGitコマンドまとめ
Machine learning for Bioimage Pose Estimation Wiki
DL papers for Markerless tracking
- Alexander Mathis et al, Pretraining boosts out-of-domain robustness for pose estimation, arxiv
- Alexander Mathis et al, Markerless tracking of user-defined features with deep learning, arXiv:1804.03142
- Tanmay Nath, Alexander Mathis et al, Using DeepLabCut for 3D markerless pose estimation across species and behaviors, biorxiv
- Tanmay Nath, Alexander Mathis et al, Using DeepLabCut for 3D markerless pose estimation across species and behaviors, Nature Protocols volume 14, pages2152–2176(2019)
- Alexander Mathis et al, DeepLabCut: markerless pose estimation of user-defined body parts with deep learning, Nature Neuroscience volume 21, pages1281–1289(2018)
- Mackenzie Weygandt Mathis, Alexander Mathis, Deep learning tools for the measurement of animal behavior in neuroscience, Current Opinion in Neurobiology Volume 60, February 2020, Pages 1-11
