# MICCAI2019-OpenSourcePapers

**Repository Path**: junma11/MICCAI2019-OpenSourcePapers

## Basic Information

- **Project Name**: MICCAI2019-OpenSourcePapers
- **Description**: MICCAI 2019 Open Source Papers
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 1
- **Created**: 2019-11-06
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

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## README

# MICCAI 2019 Open Source Papers

## [Part I, LNCS Volume 11764](https://link.springer.com/book/10.1007/978-3-030-32239-7#volumes) Optical Imaging; Endoscopy; Microscopy 

|Title|First Author|PDF|Code|
|---|---|---|---|
|A Deep Reinforcement Learning Framework for Frame-by-Frame Plaque Tracking on Intravascular Optical Coherence Tomography Image|Gongning Luo|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_2)|[Code]( https://github.com/luogongning/PlaqueRL)|
|Boundary and Entropy-Driven Adversarial Learning for Fundus Image Segmentation|Shujun Wang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_12)|[Code]( https://github.com/EmmaW8/BEAL)|
|Probabilistic Atlases to Enforce Topological Constraints|Udaranga Wickramasinghe|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_25)|[Code](https://github.com/cvlab-epfl/PA-net.git)|
|Synapse-Aware Skeleton Generation for Neural Circuits|Brian Matejek|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_26)|[Code](https://www.rhoana.org/synapseaware)|
|Seeing Under the Cover: A Physics Guided Learning Approach for In-bed Pose Estimation|Shuangjun Liu|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_27)|[Code](https://web.northeastern.edu/ostadabbas/2019/06/27/multimodal-in-bedpose-estimation/)|
|Ki-GAN: Knowledge Infusion Generative Adversarial Network for Photoacoustic Image Reconstruction In Vivo|Hengrong Lan|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_31)|[Code](https://github.com/chenyilan/MICCAI19-Ki-GAN)|
|Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification|Xiaoqing Guo|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_33)|[Code](https://github.com/Guo-Xiaoqing/Triple-ANet)|
|Selective Feature Aggregation Network with Area-Boundary Constraints for Polyp Segmentation|Yuqi Fang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_34)|[Code]( https://github.com/Yuqi-cuhk/Polyp-Seg)|
|Multi-scale Cell Instance Segmentation with Keypoint Graph Based Bounding Boxes|Jingru Yi|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_41)|[Code](https://github.com/yijingru/KG_Instance_Segmentation)|
|Improving Nuclei/Gland Instance Segmentation in Histopathology Images by Full Resolution Neural Network and Spatial Constrained Loss|Hui Qu|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_42)|[Code](https://github.com/huiqu18/FullNet-varCE)|
|ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation|Zhijie Zhang|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_49)|[Code](https://github.com/ZzzJzzZ/ETNet)|
|Instance Segmentation of Biomedical Images with an Object-Aware Embedding Learned with Local Constraints|Long Chen|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_50)|[Code](https://github.com/looooongChen/instance_segmentation_with_pixel_embeddings/)|
|Synthetic Patches, Real Images: Screening for Centrosome Aberrations in EM Images of Human Cancer Cells|Artem Lukoyanov|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_58)|[Code](https://github.com/kreshuklab/centriole_detection)|
|Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response|Kazuya Nishimura|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_72)|[Code]( https://github.com/naivete5656/WSISPDR)|
|Robust Non-negative Tensor Factorization, Diffeomorphic Motion Correction, and Functional Statistics to Understand Fixation in Fluorescence Microscopy|Neel Dey|[LNCS](https://doi.org/10.1007/978-3-030-32239-7_73)|[Code](https://github.com/neel-dey/robustNTF)|



## [Part II, LNCS Volume 11765](https://link.springer.com/book/10.1007/978-3-030-32245-8) Image Segmentation; Image Registration; Cardiovascular Imaging; Growth, Development, Atrophy, and Progression 

|Title|First Author|PDF|Code|
|---|---|---|---|
|‘Project & Excite’ Modules for Segmentation of Volumetric Medical Scans|Anne-Marie Rickmann|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_5)|[Code](https://github.com/ai-med/squeeze_and_excitation)|
|Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation|Alain Jungo|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_6)|[Code](https://github.com/alainjungo/reliability-challenges-uncertainty)|
|Extreme Points Derived Confidence Map as a Cue for Class-Agnostic Interactive Segmentation Using Deep Neural Network|Shadab Khan|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_8)|[Code](https://github.com/ahmedshahin9/AssistedAnnotator)|
|Instance Segmentation from Volumetric Biomedical Images Without Voxel-Wise Labeling|Meng Dong|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_10)|[Code](https://braindata.bitahub.com/)|
|PHiSeg: Capturing Uncertainty in Medical Image Segmentation|Christian F. Baumgartner|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_14)|[Code](https://github.com/baumgach/PHiSeg-code)|
|Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss|Guotai Wang|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_30)|[Code](https://github.com/NifTK/VSSegmentation)|
|Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation|Fabian Balsiger|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_31)|[Code](https://github.com/fabianbalsiger/point-cloud-segmentation-miccai2019)|
|3D U2-Net: A 3D Universal U-Net for Multi-domain Medical Image Segmentation|Chao Huang|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_33)|[Code](https://github.com/huangmozhilv/u2net_torch/)|
|Constrained Domain Adaptation for Segmentation|Mathilde Bateson|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_37)|[Code](https://github.com/CDAMICCAI2019/CDA)|
|Curriculum Semi-supervised Segmentation|Hoel Kervadec|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_63)|[Code](https://github.com/LIVIAETS/semi_curriculum)|
|Uncertainty-Aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation|Lequan Yu|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_67)|[Code](https://github.com/yulequan/UA-MT)|
|Deep Probabilistic Modeling of Glioma Growth|Jens Petersen|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_89)|[Code](https://github.com/jenspetersen/probabilistic-unet)|
|Variational AutoEncoder for Regression: Application to Brain Aging Analysis|Qingyu Zhao|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_91)|[Code](https://github.com/QingyuZhao/VAE-for-Regression)|
|Disease Knowledge Transfer Across Neurodegenerative Diseases|R˘azvan V. Marinescu|[LNCS](https://doi.org/10.1007/978-3-030-32245-8_95)|[Code](https://github.com/mrazvan22/dkt)|
|One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation|Mathias Perslev|[PDF](https://link.springer.com/chapter/10.1007/978-3-030-32245-8_4)|[TF](https://github.com/perslev/MultiPlanarUNet)|
|Recursive Cascaded Networks for Unsupervised Medical Image Registration|Shengyu Zhao|[PDF](https://arxiv.org/pdf/1907.12353)|[Code](https://github.com/microsoft/Recursive-Cascaded-Networks)|
|Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks|Mattias P. Heinrich|[PDF](https://arxiv.org/abs/1907.10931v1)|[Code](https://github.com/multimodallearning/pdd_net)|

## [Part III, LNCS Volume 11766](https://link.springer.com/book/10.1007/978-3-030-32248-9) Neuroimage Reconstruction and Synthesis; Neuroimage Segmentation; Diffusion-Weighted Magnetic Resonance Imaging; Functional Neuroimaging (fMRI); Miscellaneous Neuroimaging

|Title|First Author|PDF|Code|
|---|---|---|---|
|Model-Based Convolutional De-Aliasing Network Learning for Parallel MR Imaging|Yanxia Chen|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_4)|[Code](https://github.com/yanxiachen/ConvDe-AliasingNet)|
|Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks|Gihyun Kwon|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_14)|[Code](https://github.com/cyclomon/3dbraingen)|
|Predicting the Evolution of White Matter Hyperintensities in Brain MRI Using Generative Adversarial Networks and Irregularity Map|Muhammad Febrian Rachmadi|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_17)|[Code](https://github.com/febrianrachmadi/dep-gan-im)|
|3D Dilated Multi-fiber Network for Real-Time Brain Tumor Segmentation in MRI|Chen Chen|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_21)|[Code](https://github.com/China-LiuXiaopeng/BraTS-DMFNet)|
|Refined Segmentation R-CNN: A Two-Stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants|Yalong Liu|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_22)|[Code](https://github.com/YalongLiu/Refined-Segmentation-R-CNN)|
|X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-Range Dependencies|Kehan Qi|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_28)|[Code](https://github.com/Andrewsher/X-Net)|
|CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke|Hao Yang|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_30)|[Code](https://github.com/YH0517/CLCI_Net)|
|Unsupervised Deep Learning for Bayesian Brain MRI Segmentation|Adrian V. Dalca|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_40)|[Code](http://voxelmorph.mit.edu)|
|A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation|Robin Brügger|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_48)|[Code](https://github.com/RobinBruegger/PartiallyReversibleUnet)|
|Cortical Surface Parcellation Using Spherical Convolutional Neural Networks|Prasanna Parvathaneni|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_56)|[Code](https://github.com/ilwoolyu/HSD)|
|Deep White Matter Analysis: Fast, Consistent Tractography Segmentation Across Populations and dMRI Acquisitions|Fan Zhang|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_67)|[Code](https://github.com/SlicerDMRI/DeepWMA)|
|DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography|Itay Benou|[LNCS](https://doi.org/10.1007/978-3-030-32248-9_70)|[Code](https://github.com/itaybenou/DeepTract.git)|


## [Part IV, LNCS Volume 11767](https://link.springer.com/book/10.1007/978-3-030-32251-9) Shape; Prediction; Detection and Localization; Machine Learning; Computer-Aided Diagnosis; Image Reconstruction and Synthesis 

|Title|First Author|PDF|Code|
|---|---|---|---|
|Multiple Landmark Detection Using Multi-agent Reinforcement Learning|Athanasios Vlontzos|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_29)|[Code](https://github.com/thanosvlo/MARL-for-Anatomical-Landmark-Detection)|
|Unsupervised Anomaly Localization Using Variational Auto-Encoders|David Zimmerer|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_32)|[Code](https://github.com/MIC-DKFZ/vae-anomaly-experiments)|
|Multi-stage Prediction Networks for Data Harmonization|Stefano B. Blumberg|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_45)|[Code](https://github.com/sbb-gh/)|
|Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning|Guilherme Pombo|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_47)|[Code](https://github.com/guilherme-pombo/3DPixelCNN)|
|Overcoming Data Limitation in Medical Visual Question Answering|Binh D. Nguyen|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_57)|[Code](https://github.com/aioz-ai/MICCAI19-MedVQA)|
|VS-Net: Variable Splitting Network for Accelerated Parallel MRI Reconstruction|Jinming Duan|[LNCS](https://doi.org/10.1007/978-3-030-32251-9_78)|[Code](https://github.com/j-duan/VS-Net)|
|Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis|Zongwei Zhou|[PDF](http://www.cs.toronto.edu/~liang/Publications/ModelsGenesis/MICCAI_2019_Full.pdf)|[Keras](https://github.com/MrGiovanni/ModelsGenesis)|

## [Part V, LNCS Volume 11768](https://link.springer.com/book/10.1007/978-3-030-32254-0) Computer-Assisted Interventions; MIC Meets CAI 

|Title|First Author|PDF|Code|
|---|---|---|---|
|INN: Inflated Neural Networks for IPMN Diagnosis|Rodney LaLonde|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_12)|[Code](https://github.com/lalonderodney/INN-Inflated-Neural-Nets)|
|Generating Large Labeled Data Sets for Laparoscopic Image Processing Tasks Using Unpaired Image-to-Image Translation|Micha Pfeiffer|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_14)|[Code](http://opencas.dkfz.de/image2image/)|
|Variational Shape Completion for Virtual Planning of Jaw Reconstructive Surgery|Amir H. Abdi|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_26)|[Code](https://github.com/amir-abdi/prob-shape-completion)|
|Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video|Yueming Jin|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_49)|[Code](https://github.com/keyuncheng/MF-TAPNet)|
|Hard Frame Detection and Online Mapping for Surgical Phase Recognition|Fangqiu Yi|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_50)|[Code](https://github.com/ChinaYi/miccai19)|
|Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video|Isabel Funke|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_52)|[Code](https://gitlab.com/nct_tso_public/surgical_gesture_recognition)|
|Matwo-CapsNet: A Multi-label Semantic Segmentation Capsules Network|Savinien Bonheur|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_74)|[Code](https://github.com/savinienb/Matwo-CapsNet)|
|LumiPath – Towards Real-Time Physically-Based Rendering on Embedded Devices|Laura Fink|[LNCS](https://doi.org/10.1007/978-3-030-32254-0_75)|[Code](https://github.com/lorafib/LumiPath)|



## [Part VI, LNCS Volume 11769-TBD]() Computed Tomography; X-ray Imaging

|Title|First Author|PDF|Code|
|---|---|---|---|
|||[LNCS]()|[Code]()|
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**Any contributations are welcome! Such as arxiv PDF link, new released code and so on.**