research
∙
08/20/2023
HODN: Disentangling Human-Object Feature for HOI Detection
The task of Human-Object Interaction (HOI) detection is to detect humans...
share
research
∙
08/09/2023
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation
Medical image analysis using deep learning is often challenged by limite...
research
∙
08/09/2023
Seeing in Flowing: Adapting CLIP for Action Recognition with Motion Prompts Learning
The Contrastive Language-Image Pre-training (CLIP) has recently shown re...
research
∙
07/28/2023
Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification
Finding abnormal lymph nodes in radiological images is highly important ...
research
∙
07/19/2023
SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid
Estimating displacement vector field via a cost volume computed in the f...
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
∙
07/07/2023
Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images
Radiotherapists require accurate registration of MR/CT images to effecti...
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
∙
04/01/2023
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
∙
03/30/2023
Model-agnostic explainable artificial intelligence for object detection in image data
Object detection is a fundamental task in computer vision, which has bee...
research
∙
02/11/2023
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Segmentation
Self-supervised learning (SSL) has recently achieved promising performan...
research
∙
02/01/2023
Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans
Deep learning empowers the mainstream medical image segmentation methods...
research
∙
01/31/2023
Few-Shot Object Detection via Variational Feature Aggregation
As few-shot object detectors are often trained with abundant base sample...
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
∙
12/05/2022
Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding
Automatic parsing of human anatomies at instance-level from 3D computed ...
research
∙
08/02/2022
A New Probabilistic V-Net Model with Hierarchical Spatial Feature Transform for Efficient Abdominal Multi-Organ Segmentation
Accurate and robust abdominal multi-organ segmentation from CT imaging o...
research
∙
05/25/2022
Location-free Human Pose Estimation
Human pose estimation (HPE) usually requires large-scale training data t...
research
∙
03/29/2022
SIOD: Single Instance Annotated Per Category Per Image for Object Detection
Object detection under imperfect data receives great attention recently....
research
∙
03/28/2022
Expanding Low-Density Latent Regions for Open-Set Object Detection
Modern object detectors have achieved impressive progress under the clos...
research
∙
01/26/2022
Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection
Semi-supervised object detection (SSOD) has achieved substantial progres...
research
∙
10/12/2021
Accurate and Generalizable Quantitative Scoring of Liver Steatosis from Ultrasound Images via Scalable Deep Learning
Background Aims: Hepatic steatosis is a major cause of chronic liver...
research
∙
10/10/2021
Transformer-based Dual Relation Graph for Multi-label Image Recognition
The simultaneous recognition of multiple objects in one image remains a ...
research
∙
09/23/2021
SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
In this work, we introduce a fast and accurate method for unsupervised 3...
research
∙
09/16/2021
Heterogeneous Relational Complement for Vehicle Re-identification
The crucial problem in vehicle re-identification is to find the same veh...
research
∙
07/20/2021
Discriminator-Free Generative Adversarial Attack
The Deep Neural Networks are vulnerable toadversarial exam-ples(Figure 1...
research
∙
06/16/2021
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages
Nowadays, Graph Neural Networks (GNNs) following the Message Passing par...
research
∙
05/05/2021
Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection
Measuring lesion size is an important step to assess tumor growth and mo...
research
∙
05/03/2021
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
Accurately segmenting a variety of clinically significant lesions from w...
research
∙
04/12/2021
Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
Depending on the application, radiological diagnoses can be associated w...
research
∙
03/09/2021
Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
The boundary of tumors (hepatocellular carcinoma, or HCC) contains rich ...
research
∙
02/10/2021
Memory-Associated Differential Learning
Conventional Supervised Learning approaches focus on the mapping from in...
research
∙
12/09/2020
Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
Monitoring treatment response in longitudinal studies plays an important...
research
∙
12/04/2020
Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
Radiological images such as computed tomography (CT) and X-rays render a...
research
∙
09/05/2020
Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT
Large-scale datasets with high-quality labels are desired for training a...
research
∙
08/30/2020
Deep Volumetric Universal Lesion Detection using Light-Weight Pseudo 3D Convolution and Surface Point Regression
Identifying, measuring and reporting lesions accurately and comprehensiv...
research
∙
08/29/2020
Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
Determining the spread of GTV_LN is essential in defining the respective...
research
∙
08/27/2020
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
Finding, identifying and segmenting suspicious cancer metastasized lymph...
research
∙
08/19/2020
CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization
Most current pipelines for spatio-temporal action localization connect f...
research
∙
08/07/2020
Reliable Liver Fibrosis Assessment from Ultrasound using Global Hetero-Image Fusion and View-Specific Parameterization
Ultrasound (US) is a critical modality for diagnosing liver fibrosis. Un...
research
∙
07/21/2020
One Click Lesion RECIST Measurement and Segmentation on CT Scans
In clinical trials, one of the radiologists' routine work is to measure ...
research
∙
06/28/2020
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning
Effective and non-invasive radiological imaging based tumor/lesion chara...
research
∙
05/28/2020
Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets
Lesion detection is an important problem within medical imaging analysis...
research
∙
05/27/2020
Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification
Finding and identifying scatteredly-distributed, small, and critically i...
research
∙
01/21/2020
Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale
Acquiring large-scale medical image data, necessary for training machine...
research
∙
08/12/2019
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
When reading medical images such as a computed tomography (CT) scan, rad...
research
∙
04/30/2019
A self-attention based deep learning method for lesion attribute detection from CT reports
In radiology, radiologists not only detect lesions from the medical imag...
research
∙
04/09/2019
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning from Radiology Reports and Label Ontology
In radiologists' routine work, one major task is to read a medical image...
research
∙
03/04/2019
Fine-grained lesion annotation in CT images with knowledge mined from radiology reports
In radiologists' routine work, one major task is to read a medical image...
research
∙
01/18/2019
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining
Automatic lesion detection from computed tomography (CT) scans is an imp...
research
∙
10/13/2018
