7 citations · 11 across the 13 of their papers we have counts for
8 papers · 1 filter
Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment
Hongyi Wang, Zhengjie Zhu, Junlin Hou +13
The rapid digitization of histopathology slides has opened new opportunities for computational tools in clinical and research workflows. Content-based slide retrieval can help path…
A Text-Image Fusion Method with Data Augmentation Capabilities for Referring Medical Image Segmentation
Shurong Chai, Rahul Kumar JAIN, Rui Xu +6
Deep learning relies heavily on data augmentation to mitigate limited data, especially in medical imaging. Recent multimodal learning integrates text and images for segmentation, k…
EPIC: Efficient Prompt Interaction for Text-Image Classification
Xinyao Yu, Hao Sun, Zeyu Ling +5
In recent years, large-scale pre-trained multimodal models (LMMs) generally emerge to integrate the vision and language modalities, achieving considerable success in multimodal tas…
TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module Exploration
Xiaoyu Shi, Rahul Kumar Jain, Yinhao Li +7
Deep learning has demonstrated remarkable success in medical image segmentation and computer-aided diagnosis. In particular, numerous advanced methods have achieved state-of-the-ar…
SemSim: Revisiting Weak-to-Strong Consistency from a Semantic Similarity Perspective for Semi-supervised Medical Image Segmentation
Shiao Xie, Hongyi Wang, Ziwei Niu +4
Semi-supervised learning (SSL) for medical image segmentation is a challenging yet highly practical task, which reduces reliance on large-scale labeled dataset by leveraging unlabe…
M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images
Hongyi Wang, Xiuju Du, Jing Liu +3
The advancement of Spatial Transcriptomics (ST) has facilitated the spatially-aware profiling of gene expressions based on histopathology images. Although ST data offers valuable i…
Language-guided Scale-aware MedSegmentor for Lesion Segmentation in Medical Imaging
Shuyi Ouyang, Jinyang Zhang, Xiangye Lin +4
In clinical practice, segmenting specific lesions based on the needs of physicians can significantly enhance diagnostic accuracy and treatment efficiency. However, conventional les…
One Framework to Rule Them All: Unifying Multimodal Tasks with LLM Neural-Tuning
Hao Sun, Yu Song, Jiaqing Liu +3
Large-scale models have exhibited remarkable capabilities across diverse domains, including automated medical services and intelligent customer support. However, as most large mode…