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DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction
Xiaoxiao He, Chaowei Tan, Ligong Han +4
Accurate 3D cardiac reconstruction from cine magnetic resonance imaging (cMRI) is crucial for improved cardiovascular disease diagnosis and understanding of the heart's motion. How…
Classification of lung cancer subtypes on CT images with synthetic pathological priors
Wentao Zhu, Yuan Jin, Gege Ma +4
The accurate diagnosis on pathological subtypes for lung cancer is of significant importance for the follow-up treatments and prognosis managements. In this paper, we propose self-…
On the Challenges and Perspectives of Foundation Models for Medical Image Analysis
Shaoting Zhang, Dimitris Metaxas
This article discusses the opportunities, applications and future directions of large-scale pre-trained models, i.e., foundation models, for analyzing medical images. Medical found…
Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation
Xiaoxiao He, Chaowei Tan, Bo Liu +8
Federated Learning has gained popularity among medical institutions since it enables collaborative training between clients (e.g., hospitals) without aggregating data. However, due…
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Di Liu, Yunhe Gao, Qilong Zhangli +8
Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis. However, due to the non-alignment char…
A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark
Yunhe Gao, Mu Zhou, Di Liu +3
Transformers have demonstrated remarkable performance in natural language processing and computer vision. However, existing vision Transformers struggle to learn from limited medic…
Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
Kexin Ding, Mu Zhou, Zichen Wang +4
Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales. The development…
Modality Bank: Learn multi-modality images across data centers without sharing medical data
Qi Chang, Hui Qu, Zhennan Yan +3
Multi-modality images have been widely used and provide comprehensive information for medical image analysis. However, acquiring all modalities among all institutes is costly and o…
Learned Half-Quadratic Splitting Network for MR Image Reconstruction
Bingyu Xin, Timothy S. Phan, Leon Axel +1
Magnetic Resonance (MR) image reconstruction from highly undersampled -space data is critical in accelerated MR imaging (MRI) techniques. In recent years, deep learning-based me…
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention
Guotai Wang, Shuwei Zhai, Giovanni Lasio +7
Computed Tomography (CT) plays an important role in monitoring radiation-induced Pulmonary Fibrosis (PF), where accurate segmentation of the PF lesions is highly desired for diagno…
FocusNetv2: Imbalanced Large and Small Organ Segmentation with Adversarial Shape Constraint for Head and Neck CT Images
Yunhe Gao, Rui Huang, Yiwei Yang +7
Radiotherapy is a treatment where radiation is used to eliminate cancer cells. The delineation of organs-at-risk (OARs) is a vital step in radiotherapy treatment planning to avoid…
Deep Learning based NAS Score and Fibrosis Stage Prediction from CT and Pathology Data
Ananya Jana, Hui Qu, Puru Rattan +3
Non-Alcoholic Fatty Liver Disease (NAFLD) is becoming increasingly prevalent in the world population. Without diagnosis at the right time, NAFLD can lead to non-alcoholic steatohep…
Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks
Qiaoying Huang, Eric Z. Chen, Hanchao Yu +4
Accurate estimation of shape thickness from medical images is crucial in clinical applications. For example, the thickness of myocardium is one of the key to cardiac disease diagno…
Enhanced MRI Reconstruction Network using Neural Architecture Search
Qiaoying Huang, Dong Yang, Yikun Xian +4
The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary comple…
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data
Qi Chang, Hui Qu, Yikai Zhang +4
In this paper, we propose a data privacy-preserving and communication efficient distributed GAN learning framework named Distributed Asynchronized Discriminator GAN (AsynDGAN). Our…
Vertebra-Focused Landmark Detection for Scoliosis Assessment
Jingru Yi, Pengxiang Wu, Qiaoying Huang +2
Adolescent idiopathic scoliosis (AIS) is a lifetime disease that arises in children. Accurate estimation of Cobb angles of the scoliosis is essential for clinicians to make diagnos…
Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation
Chaowei Tan, Zhennan Yan, Shaoting Zhang +2
The 3D morphology and quantitative assessment of knee articular cartilages (i.e., femoral, tibial, and patellar cartilage) in magnetic resonance (MR) imaging is of great importance…