Search Results for author: Yang Nan

Found 33 papers, 10 papers with code

Learning Pareto Set for Multi-Objective Continuous Robot Control

1 code implementation27 Jun 2024 Tianye Shu, Ke Shang, Cheng Gong, Yang Nan, Hisao Ishibuchi

For a control problem with multiple conflicting objectives, there exists a set of Pareto-optimal policies called the Pareto set instead of a single optimal policy.

Multi-Objective Reinforcement Learning

Deep asymmetric mixture model for unsupervised cell segmentation

no code implementations3 Jun 2024 Yang Nan, Guang Yang

To address these issues, this paper presents a novel asymmetric mixture model for unsupervised cell segmentation.

Cell Segmentation Drug Discovery +1

When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI

no code implementations15 May 2024 Xiaodan Xing, Fadong Shi, Jiahao Huang, Yinzhe Wu, Yang Nan, Sheng Zhang, Yingying Fang, Mike Roberts, Carola-Bibiane Schönlieb, Javier Del Ser, Guang Yang

There is a significant gap in the scientific literature regarding the impact of synthetic data use in generative AI, particularly in terms of the fusion of multimodal information.

Make it more specific: A novel uncertainty based airway segmentation application on 3D U-Net and its variants

no code implementations12 Feb 2024 Shiyi Wang, Yang Nan, Felder Federico N, Sheng Zhang, Walsh Simon L F, Guang Yang

The most popular algorithms in medical segmentation, 3D U-Net and its variants, can directly implement the task of lung trachea segmentation, but its failure to consider the special tree-like structure of the trachea suggests that there is much room for improvement in its segmentation accuracy.

Segmentation

Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies

no code implementations29 Jan 2024 Jiahao Huang, Yinzhe Wu, Fanwen Wang, Yingying Fang, Yang Nan, Cagan Alkan, Lei Xu, Zhifan Gao, Weiwen Wu, Lei Zhu, Zhaolin Chen, Peter Lally, Neal Bangerter, Kawin Setsompop, Yike Guo, Daniel Rueckert, Ge Wang, Guang Yang

Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans.

Federated Learning MRI Reconstruction

High Accuracy and Cost-Saving Active Learning 3D WD-UNet for Airway Segmentation

no code implementations9 Oct 2023 Shiyi Wang, Yang Nan, Simon Walsh, Guang Yang

We propose a novel Deep Active Learning (DeepAL) model-3D Wasserstein Discriminative UNet (WD-UNet) for reducing the annotation effort of medical 3D Computed Tomography (CT) segmentation.

Active Learning Computed Tomography (CT) +1

Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach

no code implementations6 Sep 2023 Yinzhe Wu, Sharon Jewell, Xiaodan Xing, Yang Nan, Anthony J. Strong, Guang Yang, Martyn G. Boutelle

This study presented a novel ultra-light-weight multi-modal deep-learning network to fuse EEG spectrogram imaging and temporal power vectors to enhance SD identification accuracy over each single electrode, allowing flexible EEG map and paving the way for SD detection on ultra-low-density EEG with variable electrode positioning.

EEG

Graph-Ensemble Learning Model for Multi-label Skin Lesion Classification using Dermoscopy and Clinical Images

no code implementations4 Jul 2023 Peng Tang, Yang Nan, Tobias Lasser

However, most methods only focus on designing a better module for multi-modal data fusion; few methods explore utilizing the label correlation between SPC and skin disease for performance improvement.

Attribute Classification +4

You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images

no code implementations25 May 2023 Xiaodan Xing, Federico Felder, Yang Nan, Giorgos Papanastasiou, Walsh Simon, Guang Yang

In addition, we have empirically demonstrated that the utility score does not require images with both high fidelity and high variety.

Data Augmentation Image Generation +1

The Beauty or the Beast: Which Aspect of Synthetic Medical Images Deserves Our Focus?

1 code implementation3 May 2023 Xiaodan Xing, Yang Nan, Federico Felder, Simon Walsh, Guang Yang

Training medical AI algorithms requires large volumes of accurately labeled datasets, which are difficult to obtain in the real world.

Effects of Archive Size on Computation Time and Solution Quality for Multi-Objective Optimization

1 code implementation7 Sep 2022 Tianye Shu, Ke Shang, Hisao Ishibuchi, Yang Nan

In this study, we examine the effects of the archive size on three aspects: (i) the quality of the selected final solution set, (ii) the total computation time for the archive maintenance and the final solution set selection, and (iii) the required memory size.

Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network

no code implementations4 Aug 2022 Yang Nan, Peng Tang, Guyue Zhang, Caihong Zeng, Zhihong Liu, Zhifan Gao, Heye Zhang, Guang Yang

However, most machine and deep learning based approaches are supervised and developed using a large number of training samples, in which the pixelwise annotations are expensive and sometimes can be impossible to obtain.

Segmentation

Large-Kernel Attention for 3D Medical Image Segmentation

no code implementations19 Jul 2022 Hao Li, Yang Nan, Javier Del Ser, Guang Yang

The performance improvement due to the proposed LK attention module was also statistically validated.

Computed Tomography (CT) Image Segmentation +4

Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectives

no code implementations12 Jul 2022 Hao Li, Zeyu Tang, Yang Nan, Guang Yang

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales.

Computed Tomography (CT)

CS$^2$: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention

1 code implementation20 Jun 2022 Xiaodan Xing, Jiahao Huang, Yang Nan, Yinzhe Wu, Chengjia Wang, Zhifan Gao, Simon Walsh, Guang Yang

The destitution of image data and corresponding expert annotations limit the training capacities of AI diagnostic models and potentially inhibit their performance.

Image Generation Segmentation

Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers

no code implementations1 Apr 2022 Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Lio, Daniel Rueckert, Yonina C. Eldar, Guang Yang

Research studies have shown no qualms about using data driven deep learning models for downstream tasks in medical image analysis, e. g., anatomy segmentation and lesion detection, disease diagnosis and prognosis, and treatment planning.

Anatomy Explainable Models +3

Automatic Fine-grained Glomerular Lesion Recognition in Kidney Pathology

no code implementations11 Mar 2022 Yang Nan, Fengyi Li, Peng Tang, Guyue Zhang, Caihong Zeng, Guotong Xie, Zhihong Liu, Guang Yang

Recognition of glomeruli lesions is the key for diagnosis and treatment planning in kidney pathology; however, the coexisting glomerular structures such as mesangial regions exacerbate the difficulties of this task.

Fine-Grained Image Classification whole slide images

Benchmarking Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization

1 code implementation18 Jan 2022 Ke Shang, Tianye Shu, Hisao Ishibuchi, Yang Nan, Lie Meng Pang

This paper aims to fill this research gap by proposing a benchmark test suite for subset selection from large candidate solution sets, and comparing some representative methods using the proposed test suite.

Benchmarking

Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation

1 code implementation31 Oct 2021 Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang

However, it is well known that the DSC loss is poorly calibrated, resulting in overconfident predictions that cannot be usefully interpreted in biomedical and clinical practice.

Image Segmentation Segmentation +1

Hypervolume-Optimal $μ$-Distributions on Line/Plane-based Pareto Fronts in Three Dimensions

no code implementations20 Apr 2021 Ke Shang, Hisao Ishibuchi, WeiYu Chen, Yang Nan, Weiduo Liao

Then, we show that a uniform solution set on the plane-based Pareto front is not always optimal for hypervolume maximization.

Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning

no code implementations20 Dec 2017 Yang Nan, Gianmarc Coppola, Qiaokang Liang, Kunglin Zou, Wei Sun, Dan Zhang, Yaonan Wang, Guanzhen Yu

Gastric cancer is the second leading cause of cancer-related deaths worldwide, and the major hurdle in biomedical image analysis is the determination of the cancer extent.

Image Segmentation Tumor Segmentation

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