E-raamat: Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

rain MR Image Segmentation in Small Dataset with Adversarial Defense and
Task Reorganization.- Spatial Regularized Classification Network for Spinal
Dislocation Diagnosis.- Globally-Aware Multiple Instance Classifier for
Breast Cancer Screening.- Advancing Pancreas Segmentation in Multi-protocol
MRI Volumes using Hausdorff-Sine Loss Function.- WSI-Net: Branch-based and
Hierarchy-aware Network for Segmentation and Classification of Breast
Histopathological Whole-slide Images.- Lesion Detection with Deep Aggregated
3D Contextual Feature and Auxiliary Information.- MSAFusionNet: Multiple
Subspace Attention Based Deep Multi-modal Fusion Network.- DCCL: A Benchmark
for Cervical Cytology Analysis.- Smartphone-Supported Malaria Diagnosis Based
on Deep Learning.- Children's Neuroblastoma Segmentation using Morphological
Features.- GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for
automatic detection of esophageal abnormalities in endoscopic images.- Deep
Active Lesion Segmentation.- Infant Brain Deformable Registration Using
Global and Local Label-Driven Deep Regression Learning.- A Relation Hashing
Network Embedded with Prior Features for Skin Lesion Classification.-
End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation.-
Privacy-preserving Federated Brain Tumour Segmentation.- Residual Attention
Generative Adversarial Networks for Nuclei Detection on Routine Colon Cancer
Histology Images.- Semi-Supervised Multi-Task Learning With Chest X-Ray
Images.- Novel Bi-directional Images Synthesis based on WGAN-GP with
GMM-based Noise Generation.- Pseudo-labeled bootstrapping and multi-stage
transfer learning for the classification and localization of dysplasia in
Barretts Esophagus.- Anatomy-Aware Self-supervised Fetal MRI Synthesis from
Unpaired Ultrasound Images.- Boundary Aware Networks for Medical Image
Segmentation.- Automatic Rodent Brain MRI Lesion Segmentation with Fully
Convolutional Networks.- Morphological Simplification of Brain MR Images by
Deep Learning for Facilitating Deformable Registration.- Joint Shape
Representation and Classification for Detecting PDAC.- FusionNet:
Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT
Scans.- Weakly supervised segmentation by a deep geodesic prior.- Ultrasound
Liver Fibrosis Diagnosis using Multi-indicator guided Deep Neural Networks.-
Correspondence-Steered Volumetric Descriptor Learning Using Deep Functional
Maps.- Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI.-
Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation.-
Automatic Couinaud Segmentation from CT Volumes on Liver Using GLC-Unet.-
Biomedical Image Segmentation by Retina-like Sequential Attention Mechanism
Using Only A Few Training Images.- Conv-MCD: A Plug-and-Play Multi-task
Module for Medical Image Segmentation.- Detecting abnormalities in
resting-state dynamics: An unsupervised learning approach.- Distanced LSTM:
Time-Distanced Gates in Long Short-Term MemoryModels for Lung Cancer
Detection.- Dense-residual Attention Network for Skin Lesion Segmentation.-
Confounder-Aware Visualization of ConvNets.- Detecting Lesion Bounding
Ellipses With Gaussian Proposal Networks.- Modelling Airway Geometry as Stock
Market Data using Bayesian Changepoint Detection.- Unsupervised Lesion
Detection with Locally Gaussian Approximation.- A Hybrid Multi-atrous and
Multi-scale Network for Liver Lesion Detection.- BOLD fMRI-based Brain
Perfusion Prediction Using Deep Dilated Wide Activation Networks.- Jointly
Discriminative and Generative Recurrent Neural Networks for Learning from
fMRI.- Unsupervised Conditional Consensus Adversarial Network for Brain
Disease Identification with Structural MRI.- A Maximum Entropy Deep
Reinforcement Learning Neural Tracker.- Weakly Supervised Confidence Learning
for Brain MR Image Dense Parcellation.- Select, Attend, and Transfer: Light,
Learnable Skip Connections.- Learning-based Bone Quality Classification
Method for Spinal Metastasis.- Automated Segmentation of Skin Lesion Based on
Pyramid Attention Network.- Relu cascade of feature pyramid networks for CT
pulmonary nodule detection.- Joint Localization of Optic Disc and Fovea in
Ultra-Widefield Fundus Images.- Multi-Scale Attentional Network for
Multi-Focal Segmentation of Active Bleed after Pelvic Fractures.- Lesion
Detection by Efficiently Bridging 3D Context.- Communal Domain Learning for
Registration in Drifted Image Spaces.- Conv2Warp: An unsupervised deformable
image registration with continuous convolution and warping.- Semantic
filtering through deep source separation on microscopy images.- Adaptive
Functional Connectivity Network using Parallel Hierarchical BiLSTM for MCI
Diagnosis.- Multi-Template based Auto-weighted Adaptive Structural Learning
for ASD Diagnosis.- Learn to Step-wise Focus on Targets for Biomedical Image
Segmentation.- Renal Cell Carcinoma Staging with Learnable Image
Histogram-based Deep Neural Network.- Weakly Supervised Learning Strategy for
Lung Defect Segmentation.- Gated Recurrent Neural Networks for Accelerated 
Ventilation MRI.- A Cascaded Multi-Modality Analysis in Mild Cognitive
Impairment.- Deep Residual Learning for Instrument Segmentation in Robotic
Surgery.- Deep learning model integrating dilated convolution and deep
supervision for brain tumor segmentation in multi-parametric MRI.- A joint 3D
UNet-Graph Neural Network-based method for Airway Segmentation from chest
CTs.- Automatic Fetal Brain Extraction Using Multi-Stage U-Net with Deep
Supervision.- Cross-Modal Attention-Guided Convolutional Network for
Multi-Modal Cardiac Segmentation.- High- and Low-Level Feature Enhancement
for Medical Image Segmentation.- Shape-Aware Complementary-Task Learning for
Multi-Organ Segmentation.- An Active Learning Approach for Reducing
Annotation Cost in Skin Lesion Analysis.- Tree-LSTM: Using LSTM to Encode
Memory in Anatomical Tree Prediction from 3D Images.- FAIM-A ConvNet Method
for Unsupervised 3D Medical Image Registration.- Functional data and long
short-term memory networks for diagnosis of Parkinson's Disease.- Joint
Holographic Detection and Reconstruction.- Reinforced Transformer for Medical
Image Captioning.- Multi Task Convolutional Neural Network for Joint Bone Age
Assessment and Ossification Center Detection from Hand Radiograph.