Multiscale Multimodal Medical Imaging First International Workshop MMMI 2019 Held in Conjunction with MICCAI 2019 Shenzhen China October 13 2019 Proceedings Quanzheng Li

Multi-modal Image Prediction via Spatial Hybrid U-Net

Automatic Segmentation of Liver CT Image Based on Dense Pyramid Network

OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images

Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data

Feature Pyramid Based Attention for Cervical Image Classification

Single-Scan Dual-Tracer Separation Network Based on Pre-trained GRU

PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation

Automated Classification of Arterioles and Venules for Retina Fundus Images Using Dual Deeply-Supervised Network

Liver Segmentation from Multimodal Images Using HED-Mask R-CNN

aEEG Signal Analysis with Ensemble Learning for Newborn Seizure Detection

Speckle Noise Removal in Ultrasound Images Using a Deep Convolutional Neural Network and a Specially Designed Loss Function

Automatic Sinus Surgery Skill Assessment Based on Instrument Segmentation and Tracking in Endoscopic Video

U-Net Training with Instance-Layer Normalization