Deep Learning for Fully Automated Prediction of Overall Survival in Patients Undergoing Resection for Pancreatic Cancer: A Retrospective Multicenter Study

Another pancreatic cancer work milestone for our group.

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Comprehensive Understanding of Dynamic Contrast-Enhanced CT Imaging and Tumor-Vascular Contact Parsing

MICCAI-MedIA (Medical Image Analysis) Special Issue of Best Papers in 2020

3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management

Nice work from our Intern. It the first work to propose a multiphase CT imaging analysis method for the full-spectrum taxonomy of pancreatic mass/disease diagnosis.

Deep learning for fully-automated prediction of overall survival in patients with oropharyngeal cancer using FDG PET imaging

My co-first authorship clinical paper on oncology.

Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging

A Contrast-Enhanced CT prediction model for PDAC.

Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networks

This is an improved version of our MICCAI 19 work.

Deep Multi-instance Learning for Survival Prediction from Whole Slide Images

Integrating 3D Geometry of Organ for Improving Medical Image Segmentation

CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT

Weakly supervised deep learning for thoracic disease classification and localization on chest x-rays

Graph CNN for survival analysis on whole slide pathological images

Cohesion-driven online actor-critic reinforcement learning for mhealth intervention

An efficient algorithm for dynamic MRI using low-rank and total variation regularizations

The extension version of MICCAI 2015. MATLAB Code is available.

A simple primal-dual algorithm for nuclear norm and total variation regularization

Wsisa: Making survival prediction from whole slide histopathological images

Use Deep learning model to predict survival from WSI.

Deep correlational learning for survival prediction from multi-modality data

Background subtraction using spatio-temporal group sparsity recovery

Subtype cell detection with an accelerated deep convolution neural network

Lung cancer survival prediction from pathological images and genetic data—An integration study

Imaging-genetic data mapping for clinical outcome prediction via supervised conditional gaussian graphical model

Imaging biomarker discovery for lung cancer survival prediction

Deep convolutional neural network for survival analysis with pathological images

Computer-assisted diagnosis of lung cancer using quantitative topology features

Background subtraction based on low-rank and structured sparse decomposition

Extension of ICME 2014, MATLAB code is available.

Accelerated dynamic MRI reconstruction with total variation and nuclear norm regularization

Foreground detection using low rank and structured sparsity