1 code implementation • 21 Nov 2024 • Delin An, Pengfei Gu, Milan Sonka, Chaoli Wang, Danny Z. Chen
To address these challenges, in this work, we propose a new SSF, called \proposed, {for segmenting any anatomical structures in 3D medical images using only a single annotated slice per training and testing volume.}
no code implementations • 16 Oct 2024 • Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen
Osteochondrodysplasia, affecting 2-3% of newborns globally, is a group of bone and cartilage disorders that often result in head malformations, contributing to childhood morbidity and reduced quality of life.
no code implementations • 13 Sep 2024 • Yaopeng Peng, Zhi Chen, Andreas Wahle, Tomas Kovarnik, Milan Sonk, Danny Z. Chen
The key manifestation of coronary artery disease (CAD) is development of fibroatheromatous plaque, the cap of which may rupture and subsequently lead to coronary artery blocking and heart attack.
no code implementations • 13 Sep 2024 • Yaopeng Peng, Milan Sonka, Danny Z. Chen
This paper introduces Spectral U-Net, a novel deep learning network based on spectral decomposition, by exploiting Dual Tree Complex Wavelet Transform (DTCWT) for down-sampling and inverse Dual Tree Complex Wavelet Transform (iDTCWT) for up-sampling.
no code implementations • 29 Jul 2024 • Yixuan Wu, Kaiyuan Hu, Qian Shao, Jintai Chen, Danny Z. Chen, Jian Wu
The advent of telemedicine represents a transformative development in leveraging technology to extend the reach of specialized medical expertise to remote surgeries, a field where the immediacy of expert guidance is paramount.
1 code implementation • 13 Jul 2024 • Jiahuan Yan, Jintai Chen, Qianxing Wang, Danny Z. Chen, Jian Wu
In our framework, a tensorized, rapidly trained GBDT feature gate, a DNN architecture pruning approach, as well as a vanilla back-propagation optimizer collaboratively train a randomly initialized MLP model.
no code implementations • 16 Jun 2024 • Pengfei Gu, Zihan Zhao, Hongxiao Wang, Yaopeng Peng, Yizhe Zhang, Nishchal Sapkota, Chaoli Wang, Danny Z. Chen
The Segment Anything Model (SAM) exhibits impressive capabilities in zero-shot segmentation for natural images.
no code implementations • 15 Jun 2024 • Pengfei Gu, Yejia Zhang, Huimin Li, Chaoli Wang, Danny Z. Chen
But, existing MAE pre-training methods, which were specifically developed with the ViT architecture, lack the ability to capture geometric shape and spatial information, which is critical for medical image segmentation tasks.
no code implementations • 18 Mar 2024 • Hongxiao Wang, Yang Yang, Zhuo Zhao, Pengfei Gu, Nishchal Sapkota, Danny Z. Chen
For predicting cancer survival outcomes, standard approaches in clinical research are often based on two main modalities: pathology images for observing cell morphology features, and genomic (e. g., bulk RNA-seq) for quantifying gene expressions.
1 code implementation • 4 Mar 2024 • Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Z. Chen, Jimeng Sun, Jian Wu, Jintai Chen
Condensing knowledge from diverse domains, language models (LMs) possess the capability to comprehend feature names from various tables, potentially serving as versatile learners in transferring knowledge across distinct tables and diverse prediction tasks, but their discrete text representation space is inherently incompatible with numerical feature values in tables.
no code implementations • 5 Feb 2024 • Suraj Mishra, Danny Z. Chen
Medical image segmentation using deep neural networks has been highly successful.
no code implementations • 5 Feb 2024 • Yixuan Wu, Kaiyuan Hu, Danny Z. Chen, Jian Wu
With the rapid advance of computer graphics and artificial intelligence technologies, the ways we interact with the world have undergone a transformative shift.
no code implementations • 15 Dec 2023 • Yizhe Zhang, Shuo Wang, Tao Zhou, Qi Dou, Danny Z. Chen
Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system.
2 code implementations • 29 Nov 2023 • Yaopeng Peng, Milan Sonka, Danny Z. Chen
We evaluate our method on several public medical image segmentation datasets for skin lesion segmentation and polyp segmentation, and the experimental results demonstrate the segmentation accuracy of our new method over state-of-the-art methods, while preserving memory and computational efficiency.
1 code implementation • 28 Nov 2023 • Yaopeng Peng, Hongxiao Wang, Milan Sonka, Danny Z. Chen
The PH module is lightweight and capable of integrating topological features into any CNN or Transformer architectures in an end-to-end fashion.
no code implementations • 24 Sep 2023 • Yixuan Wu, Bo Zheng, Jintai Chen, Danny Z. Chen, Jian Wu
As deep learning methods continue to improve medical image segmentation performance, data annotation is still a big bottleneck due to the labor-intensive and time-consuming burden on medical experts, especially for 3D images.
no code implementations • 16 Sep 2023 • Yixuan Wu, Jintai Chen, Jiahuan Yan, Yiheng Zhu, Danny Z. Chen, Jian Wu
Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden.
no code implementations • 15 Sep 2023 • Marinka Zitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T. M. Murali, Predrag Radivojac, Sushmita Roy, Anaïs Baudot, Serdar Bozdag, Danny Z. Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara Gosline, Pengfei Gu, Pietro H. Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyuturk, Jian Ma, Alexander R. Pico, Nataša Pržulj, Teresa M. Przytycka, Benjamin J. Raphael, Anna Ritz, Roded Sharan, Yang shen, Mona Singh, Donna K. Slonim, Hanghang Tong, Xinan Holly Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales.
no code implementations • 9 Sep 2023 • Yizhe Zhang, Shuo Wang, Yejia Zhang, Danny Z. Chen
Conformal prediction (CP) generates a set of predictions for a given test sample such that the prediction set almost always contains the true label (e. g., 99. 5\% of the time).
1 code implementation • 26 Aug 2023 • Yizhe Zhang, Tao Zhou, Shuo Wang, Ye Wu, Pengfei Gu, Danny Z. Chen
Our new method is iterative and consists of two main stages: (1) segmentation model training; (2) expanding the labeled set by using the trained segmentation model, an unlabeled set, SAM, and domain-specific knowledge.
1 code implementation • 23 Jul 2023 • Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Danny Z. Chen
Modern medical image segmentation methods primarily use discrete representations in the form of rasterized masks to learn features and generate predictions.
1 code implementation • 22 Apr 2023 • Yizhe Zhang, Tao Zhou, Shuo Wang, Peixian Liang, Danny Z. Chen
Thus, how to utilize such a large foundation model for medical image segmentation is an emerging research target.
no code implementations • 17 Feb 2023 • Yizhe Zhang, Danny Z. Chen
In this paper, we propose a novel approach (called GPT4MIA) that utilizes Generative Pre-trained Transformer (GPT) as a plug-and-play transductive inference tool for medical image analysis (MIA).
1 code implementation • 30 Nov 2022 • Jiahuan Yan, Jintai Chen, Yixuan Wu, Danny Z. Chen, Jian Wu
Recent development of deep neural networks (DNNs) for tabular learning has largely benefited from the capability of DNNs for automatic feature interaction.
no code implementations • 16 Nov 2022 • Yejia Zhang, Nishchal Sapkota, Pengfei Gu, Yaopeng Peng, Hao Zheng, Danny Z. Chen
Understanding of spatial attributes is central to effective 3D radiology image analysis where crop-based learning is the de facto standard.
no code implementations • 15 Nov 2022 • Pengfei Gu, Yejia Zhang, Chaoli Wang, Danny Z. Chen
(2) A residual-shaped hybrid stem based on a combination of convolutions and Enhanced DeTrans is developed to capture both local and global representations to enhance representation ability.
no code implementations • 15 Nov 2022 • Yejia Zhang, Xinrong Hu, Nishchal Sapkota, Yiyu Shi, Danny Z. Chen
Self-supervised instance discrimination is an effective contrastive pretext task to learn feature representations and address limited medical image annotations.
no code implementations • 15 Nov 2022 • Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Hao Zheng, Peixian Liang, Danny Z. Chen
High annotation costs and limited labels for dense 3D medical imaging tasks have recently motivated an assortment of 3D self-supervised pretraining methods that improve transfer learning performance.
1 code implementation • 12 Nov 2022 • Siyi Qian, Haochao Ying, Renjun Hu, Jingbo Zhou, Jintai Chen, Danny Z. Chen, Jian Wu
To address these issues, we propose a novel RTGNN (Robust Training of Graph Neural Networks via Noise Governance) framework that achieves better robustness by learning to explicitly govern label noise.
no code implementations • 4 Sep 2022 • Suraj Mishra, Yizhe Zhang, Li Zhang, Tianyu Zhang, X. Sharon Hu, Danny Z. Chen
Specifically, we analyze the convolutional network's behavior (field-of-view) to find the location of deep supervision for improved feature extraction.
no code implementations • 21 Jul 2022 • Jintai Chen, Kuanlun Liao, Kun Wei, Haochao Ying, Danny Z. Chen, Jian Wu
Electrocardiogram (ECG) is a widely used non-invasive diagnostic tool for heart diseases.
1 code implementation • 1 Jul 2022 • Yizhe Zhang, Suraj Mishra, Peixian Liang, Hao Zheng, Danny Z. Chen
We aim to quantitatively measure the practical usability of medical image segmentation models: to what extent, how often, and on which samples a model's predictions can be used/trusted.
1 code implementation • 16 Jun 2022 • Yuexin Bian, Jintai Chen, Xiaojun Chen, Xiaoxian Yang, Danny Z. Chen, Jian Wu
Automatic ECG classification methods, especially the deep learning based ones, have been proposed to detect cardiac abnormalities using ECG records, showing good potential to improve clinical diagnosis and help early prevention of cardiovascular diseases.
no code implementations • IEEE Transactions on Medical Imaging 2022 • Suraj Mishra, Yizhe Zhang, Danny Z. Chen, X. Sharon Hu
In this paper, we study medical image segmentation by focusing on robust data-specific feature extraction to achieve improved dense prediction.
no code implementations • 2 Jun 2022 • Peixian Liang, Yizhe Zhang, Yifan Ding, Jianxu Chen, Chinedu S. Madukoma, Tim Weninger, Joshua D. Shrout, Danny Z. Chen
We observe that probability maps by DL semantic segmentation models can be used to generate many possible instance candidates, and accurate instance segmentation can be achieved by selecting from them a set of "optimized" candidates as output instances.
no code implementations • 15 Feb 2022 • Yejia Zhang, Jingjing Zhang, Xiaomin Zha, Yiru Zhou, Yunxia Cao, Danny Z. Chen
With rising male infertility, sperm head morphology classification becomes critical for accurate and timely clinical diagnosis.
1 code implementation • 3 Jan 2022 • Yixuan Wu, Kuanlun Liao, Jintai Chen, Jinhong Wang, Danny Z. Chen, Honghao Gao, Jian Wu
In this paper, we propose a new method called Dilated Transformer, which conducts self-attention for pair-wise patch relations captured alternately in local and global scopes.
1 code implementation • 15 Dec 2021 • Ruiwei Feng, Yufeng Xie, Minshan Lai, Danny Z. Chen, Ji Cao, Jian Wu
Accurate drug response prediction (DRP) is a crucial yet challenging task in precision medicine.
1 code implementation • 6 Dec 2021 • Jintai Chen, Kuanlun Liao, Yao Wan, Danny Z. Chen, Jian Wu
A special basic block is built using AbstLays, and we construct a family of Deep Abstract Networks (DANets) for tabular data classification and regression by stacking such blocks.
no code implementations • 10 Jul 2021 • Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen
Unlike the current literature on task-specific self-supervised pretraining followed by supervised fine-tuning, we utilize SSL to learn task-agnostic knowledge from heterogeneous data for various medical image segmentation tasks.
no code implementations • 6 Jul 2021 • Suraj Mishra, Danny Z. Chen, X. Sharon Hu
Finally, the mapping is used to determine the convolutional layer-wise multiplicative factor for generating a compressed network.
1 code implementation • 12 May 2021 • Jintai Chen, Xiangshang Zheng, Hongyun Yu, Danny Z. Chen, Jian Wu
For the first time, we propose a new concept, Electrocardio Panorama, which allows visualizing ECG signals from any queried viewpoints.
no code implementations • 17 Apr 2021 • Suraj Mishra, Danny Z. Chen, X. Sharon Hu
In this paper, we study retinal vessel segmentation by incorporating tiny vessel segmentation into our framework for the overall accurate vessel segmentation.
no code implementations • 10 Feb 2021 • Jintai Chen, Bohan Yu, Biwen Lei, Ruiwei Feng, Danny Z. Chen, Jian Wu
The architecture of DI is designed to learn the diagnostic logistics of doctors using the scoring methods (e. g., the Tanner-Whitehouse method) for bone age assessment.
no code implementations • 9 Feb 2021 • Jintai Chen, Hongyun Yu, Ruiwei Feng, Danny Z. Chen, Jian Wu
In clinical practice, medical image interpretation often involves multi-labeled classification, since the affected parts of a patient tend to present multiple symptoms or comorbidities.
no code implementations • 17 Dec 2020 • Hongxiao Wang, Hao Zheng, Jianxu Chen, Lin Yang, Yizhe Zhang, Danny Z. Chen
Second, we devise an effective data selection policy for judiciously sampling the generated images: (1) to make the generated training set better cover the dataset, the clusters that are underrepresented in the original training set are covered more; (2) to make the training process more effective, we identify and oversample the images of "hard cases" in the data for which annotated training data may be scarce.
no code implementations • 7 Jun 2019 • Yizhe Zhang, Michael T. C. Ying, Danny Z. Chen
Ablation study confirms the effectiveness of our proposed learning scheme for medical images.
no code implementations • 28 Feb 2019 • Yizhe Zhang, Lin Yang, Hao Zheng, Peixian Liang, Colleen Mangold, Raquel G. Loreto, David. P. Hughes, Danny Z. Chen
To better mimic human visual perception, we think it is desirable for the deep learning model to be able to perceive not only raw images but also SP images.
no code implementations • 15 Jan 2019 • Peixian Liang, Jianxu Chen, Hao Zheng, Lin Yang, Yizhe Zhang, Danny Z. Chen
The cascade decoder structure aims to conduct more effective decoding of hierarchically encoded features and is more compatible with common encoders than the known decoders.
1 code implementation • 6 Jan 2019 • Suraj Mishra, Peixian Liang, Adam Czajka, Danny Z. Chen, X. Sharon Hu
Convolutional neural networks (CNNs) for biomedical image analysis are often of very large size, resulting in high memory requirement and high latency of operations.
1 code implementation • 10 Dec 2018 • Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen
In this paper, we propose a new ensemble learning framework for 3D biomedical image segmentation that combines the merits of 2D and 3D models.
Ranked #1 on
Cardiovascular MR Segmentaiton
on HVSMR 2016
no code implementations • 28 Jun 2018 • Zhuo Zhao, Lin Yang, Hao Zheng, Ian H. Guldner, Si-Yuan Zhang, Danny Z. Chen
Our approach needs only 3D bounding boxes for all instances and full voxel annotation for a small fraction of the instances, and uses a novel two-stage 3D instance segmentation model utilizing these two kinds of annotation, respectively.
no code implementations • 2 Jun 2018 • Lin Yang, Yizhe Zhang, Zhuo Zhao, Hao Zheng, Peixian Liang, Michael T. C. Ying, Anil T. Ahuja, Danny Z. Chen
In recent years, deep learning (DL) methods have become powerful tools for biomedical image segmentation.
no code implementations • 1 Feb 2018 • Peixian Liang, Jianxu Chen, Pavel A. Brodskiy, Qinfeng Wu, Yejia Zhang, Yizhe Zhang, Lin Yang, Jeremiah J. Zartman, Danny Z. Chen
A key to analyzing spatial-temporal patterns of $Ca^{2+}$ signal waves is to accurately align the pouches across image sequences.
no code implementations • 15 Jun 2017 • Lin Yang, Yizhe Zhang, Jianxu Chen, Si-Yuan Zhang, Danny Z. Chen
Image segmentation is a fundamental problem in biomedical image analysis.
no code implementations • 31 May 2017 • Jianxu Chen, Sreya Banerjee, Abhinav Grama, Walter J. Scheirer, Danny Z. Chen
We propose a new FCN-type deep learning model, called deep complete bipartite networks (CB-Net), and a new scheme for leveraging approximate instance-wise annotation to train our pixel-wise prediction model.
no code implementations • 29 May 2017 • Xiaoming Chen, Jianxu Chen, Danny Z. Chen, Xiaobo Sharon Hu
The high computation throughput and memory bandwidth of graphics processing units (GPUs) make GPUs a natural choice for accelerating convolution operations.
2 code implementations • NeurIPS 2016 • Jianxu Chen, Lin Yang, Yizhe Zhang, Mark Alber, Danny Z. Chen
Segmentation of 3D images is a fundamental problem in biomedical image analysis.
1 code implementation • 4 Jan 2013 • Danny Z. Chen, Jian Li, Hongyu Liang, Haitao Wang
We also consider the outlier version of the problem where a given number of vertices can be excluded as the outliers from the solution.
Data Structures and Algorithms Discrete Mathematics