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
DS@BioMed at ImageCLEFmedical Caption 2024: Enhanced Attention Mechanisms in Medical Caption Generation through Concept Detection Integration
Nhi Ngoc-Yen Nguyen, Le-Huy Tu, Dieu-Phuong Nguyen, Nhat-Tan Do, Minh Triet Thai, Bao-Thien Nguyen-Tat
Lightening Anything in Medical Images
Ben Fei, Yixuan Li, Weidong Yang, Hengjun Gao, Jingyi Xu, Lipeng Ma, Yatian Yang, Pinghong Zhou
Complex Style Image Transformations for Domain Generalization in Medical Images
Nikolaos Spanos, Anastasios Arsenos, Paraskevi-Antonia Theofilou, Paraskevi Tzouveli, Athanasios Voulodimos, Stefanos Kollias
A study on the adequacy of common IQA measures for medical images
Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Thomas R Else, Timothy J Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
A study of why we need to reassess full reference image quality assessment with medical images
Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb
Understanding differences in applying DETR to natural and medical images
Yanqi Xu, Yiqiu Shen, Carlos Fernandez-Granda, Laura Heacock, Krzysztof J. Geras
Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images
Syed Javed, Tariq M. Khan, Abdul Qayyum, Hamid Alinejad-Rokny, Arcot Sowmya, Imran Razzak
UIT-DarkCow team at ImageCLEFmedical Caption 2024: Diagnostic Captioning for Radiology Images Efficiency with Transformer Models
Quan Van Nguyen, Huy Quang Pham, Dan Quang Tran, Thang Kien-Bao Nguyen, Nhat-Hao Nguyen-Dang, Bao-Thien Nguyen-Tat
Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction
Yuyang Xue, Jingshuai Liu, Steven McDonagh, Sotirios A. Tsaftaris
PriCE: Privacy-Preserving and Cost-Effective Scheduling for Parallelizing the Large Medical Image Processing Workflow over Hybrid Clouds
Yuandou Wang, Neel Kanwal, Kjersti Engan, Chunming Rong, Paola Grosso, Zhiming Zhao