29 citations · 104 across the 31 of their papers we have counts for
13 papers · 1 filter
DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction
Cuong Tran Van, Trong-Thang Pham, Ngoc-Son Nguyen +2
Sparse-view Cone-Beam Computed Tomography reconstruction from limited X-ray projections remains a challenging problem in medical imaging due to the inherent undersampling of fine-g…
How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
Tuan Anh Tran, Duy M. H. Nguyen, Hoai-Chau Tran +7
Recent advances in 3D point cloud transformers have led to state-of-the-art results in tasks such as semantic segmentation and reconstruction. However, these models typically rely…
Aleatoric Uncertainty Medical Image Segmentation Estimation via Flow Matching
Phi Van Nguyen, Ngoc Huynh Trinh, Duy Minh Lam Nguyen +2
Quantifying aleatoric uncertainty in medical image segmentation is critical since it is a reflection of the natural variability observed among expert annotators. A conventional app…
MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification
Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep +7
Whole slide pathology image classification presents challenges due to gigapixel image sizes and limited annotation labels, hindering model generalization. This paper introduces a p…
I-MPN: Inductive Message Passing Network for Efficient Human-in-the-Loop Annotation of Mobile Eye Tracking Data
Hoang H. Le, Duy M. H. Nguyen, Omair Shahzad Bhatti +5
Comprehending how humans process visual information in dynamic settings is crucial for psychology and designing user-centered interactions. While mobile eye-tracking systems combin…
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model
Duy M. H. Nguyen, An T. Le, Trung Q. Nguyen +7
Prompt learning methods are gaining increasing attention due to their ability to customize large vision-language models to new domains using pre-trained contextual knowledge and mi…
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Duy M. H. Nguyen, Hoang Nguyen, Nghiem T. Diep +9
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained dee…
DRG-Net: Interactive Joint Learning of Multi-lesion Segmentation and Classification for Diabetic Retinopathy Grading
Hasan Md Tusfiqur, Duy M. H. Nguyen, Mai T. N. Truong +8
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world, and early DR detection is necessary to prevent vision loss and support an appropriate treatment. In this w…
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Duy M. H. Nguyen, Hoang Nguyen, Mai T. N. Truong +7
Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs i…
LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Object Tracking
Duy M. H. Nguyen, Roberto Henschel, Bodo Rosenhahn +2
Multi-Camera Multi-Object Tracking is currently drawing attention in the computer vision field due to its superior performance in real-world applications such as video surveillance…
Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction
Duy M. H. Nguyen, Truong T. N. Mai, Ngoc T. T. Than +2
This paper investigates the problem of domain adaptation for diabetic retinopathy (DR) grading. We learn invariant target-domain features by defining a novel self-supervised task b…
TATL: Task Agnostic Transfer Learning for Skin Attributes Detection
Duy M. H. Nguyen, Thu T. Nguyen, Huong Vu +4
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approache…
ASMCNN: An Efficient Brain Extraction Using Active Shape Model and Convolutional Neural Networks
Duy H. M. Nguyen, Duy M. Nguyen, Mai T. N. Truong +5
Brain extraction (skull stripping) is a challenging problem in neuroimaging. It is due to the variability in conditions from data acquisition or abnormalities in images, making bra…