Medical Image
Medical image analysis focuses on extracting meaningful information from various imaging modalities (e.g., CT, MRI, X-ray) to improve diagnosis and treatment planning. Current research emphasizes developing robust and efficient algorithms, often employing convolutional neural networks (CNNs), transformers, and diffusion models, to address challenges like data variability, limited annotations, and privacy concerns. These advancements are crucial for improving the accuracy and speed of medical image analysis, leading to better patient care and accelerating medical research.
Papers
Leveraging image captions for selective whole slide image annotation
Jingna Qiu, Marc Aubreville, Frauke Wilm, Mathias Öttl, Jonas Utz, Maja Schlereth, Katharina Breininger
Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports
Yutong Zhang, Yi Pan, Tianyang Zhong, Peixin Dong, Kangni Xie, Yuxiao Liu, Hanqi Jiang, Zhengliang Liu, Shijie Zhao, Tuo Zhang, Xi Jiang, Dinggang Shen, Tianming Liu, Xin Zhang
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions
Hareem Nisar, Syed Muhammad Anwar, Zhifan Jiang, Abhijeet Parida, Ramon Sanchez-Jacob, Vishwesh Nath, Holger R. Roth, Marius George Linguraru
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scans
Gabriele Lozupone, Alessandro Bria, Francesco Fontanella, Frederick J.A. Meijer, Claudio De Stefano
Towards a Holistic Framework for Multimodal Large Language Models in Three-dimensional Brain CT Report Generation
Cheng-Yi Li, Kao-Jung Chang, Cheng-Fu Yang, Hsin-Yu Wu, Wenting Chen, Hritik Bansal, Ling Chen, Yi-Ping Yang, Yu-Chun Chen, Shih-Pin Chen, Jiing-Feng Lirng, Kai-Wei Chang, Shih-Hwa Chiou
A Data-Driven Guided Decoding Mechanism for Diagnostic Captioning
Panagiotis Kaliosis, John Pavlopoulos, Foivos Charalampakos, Georgios Moschovis, Ion Androutsopoulos
Gaze-directed Vision GNN for Mitigating Shortcut Learning in Medical Image
Shaoxuan Wu, Xiao Zhang, Bin Wang, Zhuo Jin, Hansheng Li, Jun Feng