research
∙
08/01/2023
Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Integrating Neural Distance and Texture-Aware Transformer
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in whi...
share
research
∙
07/20/2023
Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists
Lung cancer is a leading cause of death worldwide and early screening is...
research
∙
07/17/2023
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network
Liver tumor segmentation and classification are important tasks in compu...
research
∙
07/10/2023
Cluster-Induced Mask Transformers for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans
Gastric cancer is the third leading cause of cancer-related mortality wo...
research
∙
06/28/2023
A Cascaded Approach for ultraly High Performance Lesion Detection and False Positive Removal in Liver CT Scans
Liver cancer has high morbidity and mortality rates in the world. Multi-...
research
∙
04/03/2023
An Efficient Learning-Based Solver for Two-Stage DC Optimal Power Flow with Feasibility Guarantees
In this paper, we consider the scenario-based two-stage stochastic DC op...
research
∙
04/01/2023
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization
Real-world medical image segmentation has tremendous long-tailed complex...
research
∙
03/02/2023
Meta-information-aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesions in Multi-phase CT
Pancreatic cancer is one of the leading causes of cancer-related death. ...
research
∙
02/25/2023
A Bottom-Up Approach to a Unified Semantic Interface for Verified Compositional Compilation
Verified compositional compilation (VCC) is a notion of modular verifica...
research
∙
01/28/2023
Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Human readers or radiologists routinely perform full-body multi-organ mu...
research
∙
01/04/2023
A deep local attention network for pre-operative lymph node metastasis prediction in pancreatic cancer via multiphase CT imaging
Lymph node (LN) metastasis status is one of the most critical prognostic...
research
∙
12/19/2022
FedTADBench: Federated Time-Series Anomaly Detection Benchmark
Time series anomaly detection strives to uncover potential abnormal beha...
research
∙
01/13/2022
SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data
Manually annotating complex scene point cloud datasets is both costly an...
research
∙
10/04/2021
Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach
Using deep neural networks to predict the solutions of AC optimal power ...
research
∙
08/23/2021
CANet: A Context-Aware Network for Shadow Removal
In this paper, we propose a novel two-stage context-aware network named ...
research
∙
06/20/2021
Fast PDN Impedance Prediction Using Deep Learning
Modeling and simulating a power distribution network (PDN) for printed c...
research
∙
03/23/2021
Automated Discovery of Real-Time Network Camera Data From Heterogeneous Web Pages
Reduction in the cost of Network Cameras along with a rise in connectivi...
research
∙
12/08/2020
3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management
The pancreatic disease taxonomy includes ten types of masses (tumors or ...
research
∙
08/26/2020
DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
research
∙
08/24/2020
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Accurate and automated tumor segmentation is highly desired since it has...
research
∙
06/10/2020
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
Deep neural network (DNN) based approaches have been widely investigated...
research
∙
05/28/2020
Self-supervised Modal and View Invariant Feature Learning
Most of the existing self-supervised feature learning methods for 3D dat...
research
∙
04/13/2020
Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences
The success of supervised learning requires large-scale ground truth lab...
research
∙
11/20/2019
RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removal
Residual images and illumination estimation have been proved very helpfu...
research
∙
10/02/2019
Weakly supervised segmentation from extreme points
Annotation of medical images has been a major bottleneck for the develop...
research
∙
08/04/2019
ARGAN: Attentive Recurrent Generative Adversarial Network for Shadow Detection and Removal
In this paper we propose an attentive recurrent generative adversarial n...
research
∙
07/08/2019
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
Radiogenomic map linking image features and gene expression profiles is ...
research
∙
06/07/2019
When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation
Recent advances in deep learning for medical image segmentation demonstr...
research
∙
04/28/2019
Unsupervised Feature Learning for Point Cloud by Contrasting and Clustering With Graph Convolutional Neural Network
To alleviate the cost of collecting and annotating large-scale point clo...
research
∙
02/23/2019
Spatial-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data
Prognostic tumor growth modeling via medical imaging observations is a c...
research
∙
10/24/2018
Solving Poisson's Equation using Deep Learning in Particle Simulation of PN Junction
Simulating the dynamic characteristics of a PN junction at the microscop...
research
∙
10/14/2018
Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks
Fine-grained classification of cervical cells into different abnormality...
research
∙
01/25/2018
DeepPap: Deep Convolutional Networks for Cervical Cell Classification
Automation-assisted cervical screening via Pap smear or liquid-based cyt...
research
∙
01/25/2018
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by in...
research
∙
01/25/2018
Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation
Image segmentation is a fundamental problem in medical image analysis. I...
research
∙
01/25/2018
Convolutional Invasion and Expansion Networks for Tumor Growth Prediction
Tumor growth is associated with cell invasion and mass-effect, which are...
research
∙
11/28/2017
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database
Radiologists in their daily work routinely find and annotate significant...
research
∙
06/01/2017
