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Youdan Feng

Explore the profile of Youdan Feng including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 17
Citations 47
Followers 0
Related Specialties
Medical Informatics
Biomedical Engineering
Biophysics
Top 10 Co-Authors
Fan Song
Guanglei Zhang
Peng Zhang
Chenbin Ma
Yangyang Sun
Tianyi Zhang
Yufang He
Guangda Fan
Fei Liu
Zeyu Liu
Published In
IEEE J Biomed Health Inform
Comput Methods Programs Biomed
Phys Med Biol
Med Phys
IEEE Trans Med Imaging
Affiliations
Soon will be listed here.
Recent Articles
1.
PST-Diff: Achieving High-Consistency Stain Transfer by Diffusion Models With Pathological and Structural Constraints
He Y, Liu Z, Qi M, Ding S, Zhang P, Song F, et al.
IEEE Trans Med Imaging . 2024 Jul; 43(10):3634-3647. PMID: 39024079
Histopathological examinations heavily rely on hematoxylin and eosin (HE) and immunohistochemistry (IHC) staining. IHC staining can offer more accurate diagnostic details but it brings significant financial and time costs. Furthermore,...
2.
SI-ViT: Shuffle instance-based Vision Transformer for pancreatic cancer ROSE image classification
Zhang T, Feng Y, Zhao Y, Lei Y, Ying N, Song F, et al.
Comput Methods Programs Biomed . 2023 Dec; 244:107969. PMID: 38064958
Background And Objective: The rapid on-site evaluation (ROSE) technique improves pancreatic cancer diagnosis by enabling immediate analysis of fast-stained cytopathological images. Automating ROSE classification could not only reduce the burden...
3.
PPG-based Continuous BP Waveform Estimation Using Polarized Attention-guided Conditional Adversarial Learning Model
Ma C, Xu Y, Zhang P, Song F, Sun Y, Feng Y, et al.
IEEE J Biomed Health Inform . 2023 Oct; PP. PMID: 37831570
The blood pressure (BP) waveform is a vital source of physiological and pathological information concerning the cardiovascular system. This study proposes a novel attention-guided conditional generative adversarial network (cGAN), named...
4.
A Novel Feature Engineering Method Based on Latent Representation Learning for Radiomics: Application in NSCLC Subtype Classification
Song F, Tian J, Zhang P, Ma C, Sun Y, Feng Y, et al.
IEEE J Biomed Health Inform . 2023 Jun; PP. PMID: 37368801
Radiomics refers to the high-throughput extraction of quantitative features from medical images, and is widely used to construct machine learning models for the prediction of clinical outcomes, while feature engineering...
5.
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer
Zhang T, Feng Y, Zhao Y, Fan G, Yang A, Lyu S, et al.
IEEE J Biomed Health Inform . 2023 Apr; PP. PMID: 37018254
Pancreatic cancer is one of the most malignant cancers with high mortality. The rapid on-site evaluation (ROSE) technique can significantly accelerate the diagnostic workflow of pancreatic cancer by immediately analyzing...
6.
Robust reconstruction of fluorescence molecular tomography based on adaptive adversarial learning strategy
Zhang P, Song F, Ma C, Liu Z, Wu H, Sun Y, et al.
Phys Med Biol . 2023 Jan; 68(4). PMID: 36696695
Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of tumor probes in small animals. However, traditional deep learning reconstruction methods that aim...
7.
Radiomics feature analysis and model research for predicting histopathological subtypes of non-small cell lung cancer on CT images: A multi-dataset study
Song F, Song X, Feng Y, Fan G, Sun Y, Zhang P, et al.
Med Phys . 2023 Jan; 50(7):4351-4365. PMID: 36682051
Purpose: Classifying the subtypes of non-small cell lung cancer (NSCLC) is essential for clinically adopting optimal treatment strategies and improving clinical outcomes, but the histological subtypes are confirmed by invasive...
8.
D2-RecST: Dual-domain joint reconstruction strategy for fluorescence molecular tomography based on image domain and perception domain
Zhang P, Ma C, Song F, Zhang T, Sun Y, Feng Y, et al.
Comput Methods Programs Biomed . 2022 Dec; 229:107293. PMID: 36481532
Background And Objective: Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of fluorescent probes in small animals. Over the past few years,...
9.
Multi-branch attention prior based parameterized generative adversarial network for fast and accurate limited-projection reconstruction in fluorescence molecular tomography
Zhang P, Ma C, Song F, Liu Z, Feng Y, Sun Y, et al.
Biomed Opt Express . 2022 Nov; 13(10):5327-5343. PMID: 36425627
Limited-projection fluorescence molecular tomography (FMT) allows rapid reconstruction of the three-dimensional (3D) distribution of fluorescent targets within a shorter data acquisition time. However, the limited-projection FMT is severely ill-posed and...
10.
Prior Attention Network for Multi-Lesion Segmentation in Medical Images
Zhao X, Zhang P, Song F, Ma C, Fan G, Sun Y, et al.
IEEE Trans Med Imaging . 2022 Aug; 41(12):3812-3823. PMID: 35939461
The accurate segmentation of multiple types of lesions from adjacent tissues in medical images is significant in clinical practice. Convolutional neural networks (CNNs) based on the coarse-to-fine strategy have been...