research
∙
09/16/2023
GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels
Since annotating medical images for segmentation tasks commonly incurs e...
share
research
∙
09/09/2023
RR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification
Conformal prediction (CP) generates a set of predictions for a given tes...
research
∙
08/26/2023
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation
The Segment Anything Model (SAM) exhibits a capability to segment a wide...
research
∙
07/23/2023
SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings
Modern medical image segmentation methods primarily use discrete represe...
research
∙
04/22/2023
Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model
The Segment Anything Model (SAM) is a recently developed large model for...
research
∙
02/17/2023
GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as A Plug-and-Play Transductive Model for Medical Image Analysis
In this paper, we propose a novel approach (called GPT4MIA) that utilize...
research
∙
11/30/2022
T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction
Recent development of deep neural networks (DNNs) for tabular learning h...
research
∙
11/16/2022
Keep Your Friends Close Enemies Farther: Debiasing Contrastive Learning with Spatial Priors in 3D Radiology Images
Understanding of spatial attributes is central to effective 3D radiology...
research
∙
11/15/2022
ConvFormer: Combining CNN and Transformer for Medical Image Segmentation
Convolutional neural network (CNN) based methods have achieved great suc...
research
∙
11/15/2022
Unsupervised Feature Clustering Improves Contrastive Representation Learning for Medical Image Segmentation
Self-supervised instance discrimination is an effective contrastive pret...
research
∙
11/15/2022
A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning
High annotation costs and limited labels for dense 3D medical imaging ta...
research
∙
11/12/2022
Robust Training of Graph Neural Networks via Noise Governance
Graph Neural Networks (GNNs) have become widely-used models for semi-sup...
research
∙
09/04/2022
Data-Driven Deep Supervision for Skin Lesion Classification
Automatic classification of pigmented, non-pigmented, and depigmented no...
research
∙
07/21/2022
ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases
Electrocardiogram (ECG) is a widely used non-invasive diagnostic tool fo...
research
∙
07/01/2022
Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models
We aim to quantitatively measure the practical usability of medical imag...
research
∙
06/16/2022
Identifying Electrocardiogram Abnormalities Using a Handcrafted-Rule-Enhanced Neural Network
A large number of people suffer from life-threatening cardiac abnormalit...
research
∙
06/02/2022
H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation
Deep learning (DL) based semantic segmentation methods have achieved exc...
research
∙
01/03/2022
D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation
Computer-aided medical image segmentation has been applied widely in dia...
research
∙
12/06/2021
DANets: Deep Abstract Networks for Tabular Data Classification and Regression
Tabular data are ubiquitous in real world applications. Although many co...
research
∙
07/10/2021
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
A large labeled dataset is a key to the success of supervised deep learn...
research
∙
07/06/2021
Image Complexity Guided Network Compression for Biomedical Image Segmentation
Compression is a standard procedure for making convolutional neural netw...
research
∙
04/17/2021
Objective-Dependent Uncertainty Driven Retinal Vessel Segmentation
From diagnosing neovascular diseases to detecting white matter lesions, ...
research
∙
02/10/2021
Doctor Imitator: A Graph-based Bone Age Assessment Framework Using Hand Radiographs
Bone age assessment is challenging in clinical practice due to the compl...
research
∙
02/09/2021
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels
In clinical practice, medical image interpretation often involves multi-...
research
∙
12/17/2020
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Automatic histopathology image segmentation is crucial to disease analys...
research
∙
06/07/2019
Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
Segmentation maps of medical images annotated by medical experts contain...
research
∙
02/28/2019
SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
Supervised training a deep neural network aims to "teach" the network to...
research
∙
01/15/2019
Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
The Encoder-Decoder architecture is a main stream deep learning model fo...
research
∙
01/06/2019
CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentation
Convolutional neural networks (CNNs) for biomedical image analysis are o...
research
∙
12/10/2018
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
3D image segmentation plays an important role in biomedical image analys...
research
∙
06/28/2018
Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation
Instance segmentation in 3D images is a fundamental task in biomedical i...
research
∙
06/02/2018
BoxNet: Deep Learning Based Biomedical Image Segmentation Using Boxes Only Annotation
In recent years, deep learning (DL) methods have become powerful tools f...
research
∙
02/01/2018
A New Registration Approach for Dynamic Analysis of Calcium Signals in Organs
Wing disc pouches of fruit flies are a powerful genetic model for studyi...
research
∙
06/15/2017
Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
Image segmentation is a fundamental problem in biomedical image analysis...
research
∙
05/31/2017
Neuron Segmentation Using Deep Complete Bipartite Networks
In this paper, we consider the problem of automatically segmenting neuro...
research
∙
09/05/2016