7 citations · 23 across the 23 of their papers we have counts for
24 papers
AURA: Unified Multimodal Framework for Conversational Music Editing
Quoc-Huy Trinh, Minh-Van Nguyen, Debesh Jha
Instruction-guided music editors typically process each request independently, limiting their ability to support workflows in which users progressively refine a track. We introduce…
Disease Burden over Skin Tone: Decomposing the Dermatology-AI Generalization Gap
Nirajan Kunwor, Sanjaya Poudel, Quoc-Huy Trinh +2
Dermatology artificial intelligence (AI) models are predominantly trained on light-skinned, cancer-focused image collections, yet they are increasingly proposed for deployment in r…
How Context Attribution Handles What the Model Already Knows
Quoc-Huy Trinh, Lin Zhu, Sebastian Szyller
Context attribution methods for large language models (LLMs) identify which input context contributes to the model response. Recent works show the initial success in attributing th…
Rad-JEPA 3D: Radiology Joint-Embedding Predictive Model for 3D Computed Tomography
Quoc-Huy Trinh, Minh-Van Nguyen, Ulas Bagci
Self-supervised pretraining is central to 3D medical image analysis, where unlabeled CT volumes are abundant but expert annotations are scarce. Yet existing volumetric encoders oft…
Firebolt-VL: Efficient Vision-Language Understanding with Cross-Modality Modulation
Quoc-Huy Trinh, Mustapha Abdullahi, Bo Zhao +1
Recent advances in multimodal large language models (MLLMs) have enabled impressive progress in vision-language understanding, yet their high computational cost limits deployment i…
Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Space
Quoc-Huy Trinh, Xi Ding, Yang Liu +7
Visual spatial intelligence is critical for medical image interpretation, yet remains largely unexplored in Multimodal Large Language Models (MLLMs) for 3D imaging. This gap persis…
Viper-F1: Fast and Fine-Grained Multimodal Understanding with Cross-Modal State-Space Modulation
Quoc-Huy Trinh
Recent advances in multimodal large language models (MLLMs) have enabled impressive progress in vision-language understanding, yet their high computational cost limits deployment i…
SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes
Jun Zeng, Quoc-Huy Trinh, Deepak Ranjan Nayak +3
Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for reducing mortality rates. However, the in…
PRS-Med: Position Reasoning Segmentation in Medical Imaging
Quoc-Huy Trinh, Minh-Van Nguyen, Jun Zeng +2
Prompt-based medical image segmentation has rapidly emerged, yet existing methods rely on explicit prompts like bounding boxes and struggle to reason about the spatial relationship…
Sing-On-Your-Beat: Simple Text-Controllable Accompaniment Generations
Quoc-Huy Trinh, Minh-Van Nguyen, Trong-Hieu Nguyen Mau +2
Singing is one of the most cherished forms of human entertainment. However, creating a beautiful song requires an accompaniment that complements the vocals and aligns well with the…
NeIn: Telling What You Don't Want
Nhat-Tan Bui, Dinh-Hieu Hoang, Quoc-Huy Trinh +3
Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, minimal research has focused on negation within text-guided…
PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy
Debesh Jha, Nikhil Kumar Tomar, Vanshali Sharma +19
Colonoscopy is the primary method for examination, detection, and removal of polyps. However, challenges such as variations among the endoscopists' skills, bowel quality preparatio…
SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation
Quoc-Huy Trinh, Hai-Dang Nguyen, Bao-Tram Nguyen Ngoc +3
Polyp segmentation, a critical concern in medical imaging, has prompted numerous proposed methods aimed at enhancing the quality of segmented masks. While current state-of-the-art…
ALGNet: Attention Light Graph Memory Network for Medical Recommendation System
Minh-Van Nguyen, Duy-Thinh Nguyen, Quoc-Huy Trinh +1
Medication recommendation is a vital task for improving patient care and reducing adverse events. However, existing methods often fail to capture the complex and dynamic relationsh…
KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation
Quoc-Huy Trinh, Minh-Van Nguyen, Phuoc-Thao Vo Thi
Polyp segmentation, a contentious issue in medical imaging, has seen numerous proposed methods aimed at improving the quality of segmented masks. While current state-of-the-art tec…
PGDS: Pose-Guidance Deep Supervision for Mitigating Clothes-Changing in Person Re-Identification
Quoc-Huy Trinh, Nhat-Tan Bui, Dinh-Hieu Hoang +6
Person Re-Identification (Re-ID) task seeks to enhance the tracking of multiple individuals by surveillance cameras. It supports multimodal tasks, including text-based person retri…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation
Quoc-Huy Trinh, Nhat-Tan Bui, Trong-Hieu Nguyen Mau +4
Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes. However, these techniques often confront…
Meta-Polyp: a baseline for efficient Polyp segmentation
Quoc-Huy Trinh
In recent years, polyp segmentation has gained significant importance, and many methods have been developed using CNN, Vision Transformer, and Transformer techniques to achieve com…
Multi Kernel Positional Embedding ConvNeXt for Polyp Segmentation
Trong-Hieu Nguyen Mau, Quoc-Huy Trinh, Nhat-Tan Bui +2
Medical image segmentation is the technique that helps doctor view and has a precise diagnosis, particularly in Colorectal Cancer. Specifically, with the increase in cases, the dia…
EfficientNet for Brain-Lesion classification
Quoc-Huy Trinh, Trong-Hieu Nguyen Mau, Radmir Zosimov +1
In the development of technology, there are increasing cases of brain disease, there are more treatments proposed and achieved a positive result. However, with Brain-Lesion, the ea…
Res-Dense Net for 3D Covid Chest CT-scan classification
Quoc-Huy Trinh, Minh-Van Nguyen, Thien-Phuc Nguyen Dinh
One of the most contentious areas of research in Medical Image Preprocessing is 3D CT-scan. With the rapid spread of COVID-19, the function of CT-scan in properly and swiftly diagn…
Custom Deep Neural Network for 3D Covid Chest CT-scan Classification
Quoc Huy Trinh, Minh Van Nguyen
3D CT-scan base on chest is one of the controversial topisc of the researcher nowadays. There are many tasks to diagnose the disease through CT-scan images, include Covid19. In thi…
Refined Deep Neural Network and U-Net for Polyps Segmentation
Quoc-Huy Trinh, Minh-Van Nguyen, Thiet-Gia Huynh +1
The Medico: Multimedia Task 2020 focuses on developing an efficient and accurate computer-aided diagnosis system for automatic segmentation [3]. We participate in task 1, Polyps se…