Shaoting Zhang

research

∙ 09/19/2023

UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation

Domain Adaptation (DA) is important for deep learning-based medical imag...

0 Jianghao Wu, et al. ∙

research

∙ 09/18/2023

Scribble-based 3D Multiple Abdominal Organ Segmentation via Triple-branch Multi-dilated Network with Pixel- and Class-wise Consistency

Multi-organ segmentation in abdominal Computed Tomography (CT) images is...

0 Meng Han, et al. ∙

research

∙ 09/07/2023

A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation

Although deep learning have revolutionized abdominal multi-organ segment...

0 Ziyan Huang, et al. ∙

research

∙ 08/30/2023

SAM-Med2D

The Segment Anything Model (SAM) represents a state-of-the-art research ...

0 Junlong Cheng, et al. ∙

research

∙ 08/15/2023

LLM-Mini-CEX: Automatic Evaluation of Large Language Model for Diagnostic Conversation

There is an increasing interest in developing LLMs for medical diagnosis...

0 Xiaoming Shi, et al. ∙

research

∙ 08/09/2023

Classification of lung cancer subtypes on CT images with synthetic pathological priors

The accurate diagnosis on pathological subtypes for lung cancer is of si...

0 Wentao Zhu, et al. ∙

research

∙ 07/27/2023

Text-guided Foundation Model Adaptation for Pathological Image Classification

The recent surge of foundation models in computer vision and natural lan...

0 Yunkun Zhang, et al. ∙

research

∙ 07/22/2023

Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction

Survival outcome assessment is challenging and inherently associated wit...

0 Kexin Ding, et al. ∙

research

∙ 06/29/2023

MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset

Pretraining with large-scale 3D volumes has a potential for improving th...

0 Guotai Wang, et al. ∙

research

∙ 06/29/2023

Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train

Foundation models have exhibited remarkable success in various applicati...

0 Zhao Wang, et al. ∙

research

∙ 06/25/2023

Exploring Data Redundancy in Real-world Image Classification through Data Selection

Deep learning models often require large amounts of data for training, l...

0 Zhenyu Tang, et al. ∙

research

∙ 06/20/2023

UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation

Accurate segmentation of the fetal brain from Magnetic Resonance Image (...

0 Jia Fu, et al. ∙

research

∙ 06/09/2023

On the Challenges and Perspectives of Foundation Models for Medical Image Analysis

This article discusses the opportunities, applications and future direct...

0 Shaoting Zhang, et al. ∙

research

∙ 06/04/2023

Training Like a Medical Resident: Universal Medical Image Segmentation via Context Prior Learning

A major enduring focus of clinical workflows is disease analytics and di...

0 Yunhe Gao, et al. ∙

research

∙ 05/30/2023

Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics

Local hemodynamic forces play an important role in determining the funct...

0 Ziyu Ni, et al. ∙

research

∙ 05/30/2023

ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models

Large pre-trained vision-language models have shown great prominence in ...

0 Huahui Yi, et al. ∙

research

∙ 05/30/2023

Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions

Segmentation of pathological images is a crucial step for accurate cance...

0 Lanfeng Zhong, et al. ∙

research

∙ 04/28/2023

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

The Segment Anything Model (SAM) made an eye-catching debut recently and...

0 Dongjie Cheng, et al. ∙

research

∙ 04/13/2023

STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training

Large-scale models pre-trained on large-scale datasets have profoundly a...

0 Ziyan Huang, et al. ∙

research

∙ 03/12/2023

Towards General Purpose Medical AI: Continual Learning Medical Foundation Model

Inevitable domain and task discrepancies in real-world scenarios can imp...

0 Huahui Yi, et al. ∙

research

∙ 11/22/2022

CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation

Generalization to previously unseen images with potential domain shifts ...

0 Ran Gu, et al. ∙

research

∙ 08/19/2022

PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation

Background and Objective: Existing deep learning platforms for medical i...

15 Guotai Wang, et al. ∙

research

∙ 08/11/2022

PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation

The success of Convolutional Neural Networks (CNNs) in 3D medical image ...

18 Shuwei Zhai, et al. ∙

research

∙ 06/08/2022

Towards Self-supervised and Weight-preserving Neural Architecture Search

Neural architecture search (NAS) algorithms save tremendous labor from h...

16 Zhuowei Li, et al. ∙

research

∙ 06/07/2022

HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy

Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABC...

0 Hao Fu, et al. ∙

research

∙ 03/04/2022

Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

Medical image segmentation plays an irreplaceable role in computer-assis...

0 Xiangde Luo, et al. ∙

research

∙ 02/17/2022

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications

Image-based characterization and disease understanding involve integrati...

0 Kexin Ding, et al. ∙

research

∙ 01/21/2022

Contrastive and Selective Hidden Embeddings for Medical Image Segmentation

Medical image segmentation has been widely recognized as a pivot procedu...

9 Zhuowei Li, et al. ∙

research

∙ 12/09/2021

Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer

Recently, deep learning with Convolutional Neural Networks (CNNs) and Tr...

0 Xiangde Luo, et al. ∙

research

∙ 09/29/2021

Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention

Computed Tomography (CT) plays an important role in monitoring radiation...

0 Guotai Wang, et al. ∙

research

∙ 09/18/2021

Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

Domain generalizable model is attracting increasing attention in medical...

0 Ran Gu, et al. ∙

research

∙ 07/08/2021

Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation

Precise localization of polyp is crucial for early cancer screening in g...

0 Lingyun Wu, et al. ∙

research

∙ 07/02/2021

Mixed Supervision Learning for Whole Slide Image Classification

Weak supervision learning on classification labels has demonstrated high...

2 Jiahui Li, et al. ∙

research

∙ 06/28/2021

Multi-Compound Transformer for Accurate Biomedical Image Segmentation

The recent vision transformer(i.e.for image classification) learns non-l...

0 Yuanfeng Ji, et al. ∙

research

∙ 05/27/2021

Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation

Deep learning has demonstrated significant improvements in medical image...

0 Jinxi Xiang, et al. ∙

research

∙ 05/14/2021

Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction

The study of multi-type Protein-Protein Interaction (PPI) is fundamental...

0 Guofeng Lv, et al. ∙

research

∙ 04/12/2021

SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching

Automatic and accurate lung nodule detection from 3D Computed Tomography...

8 Xiangde Luo, et al. ∙

research

∙ 02/03/2021

Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss

Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) ...

10 Wenhui Lei, et al. ∙

research

∙ 12/29/2020

Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning

Despite that deep learning has achieved state-of-the-art performance for...

38 Lu Wang, et al. ∙

research

∙ 12/13/2020

One-Shot Object Localization in Medical Images based on Relative Position Regression

Deep learning networks have shown promising performance for accurate obj...

0 Wenhui Lei, et al. ∙

research

∙ 12/13/2020

Semi-supervised Segmentation via Uncertainty Rectified Pyramid Consistency and Its Application to Gross Target Volume of Nasopharyngeal Carcinoma

Gross Target Volume (GTV) segmentation plays an irreplaceable role in ra...

0 Xiangde Luo, et al. ∙

research

∙ 11/01/2020

Learning Euler's Elastica Model for Medical Image Segmentation

Image segmentation is a fundamental topic in image processing and has be...

19 Xu Chen, et al. ∙

research

∙ 09/16/2020

UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation

Aggregating multi-level feature representation plays a critical role in ...

0 Yuanfeng Ji, et al. ∙

research

∙ 09/09/2020

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Deep learning-based semi-supervised learning (SSL) algorithms have led t...

12 Xiangde Luo, et al. ∙

research

∙ 08/17/2020

Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets

Multi-organ segmentation has extensive applications in many clinical app...

18 Rui Huang, et al. ∙

research

∙ 07/10/2020

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images

Nuclei segmentation is a fundamental task in histopathology image analys...

12 Hui Qu, et al. ∙

research

∙ 07/07/2020

Automatic Ischemic Stroke Lesion Segmentation from Computed Tomography Perfusion Images by Image Synthesis and Attention-Based Deep Neural Networks

Ischemic stroke lesion segmentation from Computed Tomography Perfusion (...

0 Guotai Wang, et al. ∙

research

∙ 05/27/2020

Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation

The segmentation of coronary arteries in X-ray angiograms by convolution...

3 Jingyang Zhang, et al. ∙

research

∙ 04/03/2020

SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization

Clinical research on smart healthcare has an increasing demand for intel...

0 Qi Duan, et al. ∙

research

∙ 10/16/2019

CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation

Recently, deep neural networks have demonstrated comparable and even bet...

0 Peng Liu, et al. ∙

Shaoting Zhang

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