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Related papers: One Model to Synthesize Them All: Multi-contrast M…

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Magnetic resonance imaging (MRI) can present multi-contrast images of the same anatomical structures, enabling multi-contrast super-resolution (SR) techniques. Compared with SR reconstruction using a single-contrast, multi-contrast SR…

Image and Video Processing · Electrical Eng. & Systems 2022-03-29 Guangyuan Li , Jun Lv , Yapeng Tian , Qi Dou , Chengyan Wang , Chenliang Xu , Jing Qin

Magnetic Resonance Imaging (MRI) is instrumental in clinical diagnosis, offering diverse contrasts that provide comprehensive diagnostic information. However, acquiring multiple MRI contrasts is often constrained by high costs, long…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Sanuwani Dayarathna , Kh Tohidul Islam , Bohan Zhuang , Guang Yang , Jianfei Cai , Meng Law , Zhaolin Chen

Synthesizing missing modalities in multi-modal magnetic resonance imaging (MRI) is vital for ensuring diagnostic completeness, particularly when full acquisitions are infeasible due to time constraints, motion artifacts, and patient…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yue Zhang , Zhizheng Zhuo , Siyao Xu , Shan Lv , Zhaoxi Liu , Jun Qiu , Qiuli Wang , Yaou Liu , S. Kevin Zhou

Multi-modal brain magnetic resonance imaging (MRI) plays a crucial role in clinical diagnostics by providing complementary information across different imaging modalities. However, a common challenge in clinical practice is missing MRI…

Image and Video Processing · Electrical Eng. & Systems 2025-06-04 Haowen Pang , Weiyan Guo , Chuyang Ye

Acquiring images of the same anatomy with multiple different contrasts increases the diversity of diagnostic information available in an MR exam. Yet, scan time limitations may prohibit acquisition of certain contrasts, and images for some…

Computer Vision and Pattern Recognition · Computer Science 2018-02-06 Salman Ul Hassan Dar , Mahmut Yurt , Levent Karacan , Aykut Erdem , Erkut Erdem , Tolga Çukur

Super-resolution (SR) plays a crucial role in improving the image quality of magnetic resonance imaging (MRI). MRI produces multi-contrast images and can provide a clear display of soft tissues. However, current super-resolution methods…

Image and Video Processing · Electrical Eng. & Systems 2021-07-07 Chun-Mei Feng , Huazhu Fu , Shuhao Yuan , Yong Xu

Multi-modal medical images provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scanning time, image corruption and various imaging protocols often result in incomplete…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Yue Zhang , Chengtao Peng , Qiuli Wang , Dan Song , Kaiyan Li , S. Kevin Zhou

Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and scientific research. A significant advantage of MRI over other imaging modalities such as computed tomography (CT) and nuclear imaging is…

Image and Video Processing · Electrical Eng. & Systems 2020-02-20 Qing Lyu , Hongming Shan , Ge Wang

Multi-contrast MRI acquisitions of an anatomy enrich the magnitude of information available for diagnosis. Yet, excessive scan times associated with additional contrasts may be a limiting factor. Two mainstream approaches for enhanced scan…

Computer Vision and Pattern Recognition · Computer Science 2018-05-29 Salman Ul Hassan Dar , Mahmut Yurt , Mohammad Shahdloo , Muhammed Emrullah Ildız , Tolga Çukur

Multi-modal magnetic resonance imaging (MRI) is essential for providing complementary information about brain anatomy and pathology, leading to more accurate diagnoses. However, obtaining high-quality multi-modal MRI in a clinical setting…

Image and Video Processing · Electrical Eng. & Systems 2025-04-15 Minjoo Lim , Bogyeong Kang , Tae-Eui Kam

Multi-contrast Magnetic Resonance Imaging (MRI) generates multiple medical images with rich and complementary information for routine clinical use; however, it suffers from a long acquisition time. Recent works for accelerating MRI, mainly…

Image and Video Processing · Electrical Eng. & Systems 2022-10-28 Lin Zhao , Xiao Chen , Eric Z. Chen , Yikang Liu , Dinggang Shen , Terrence Chen , Shanhui Sun

Multi-contrast MRI sequences allow for the acquisition of images with varying tissue contrast within a single scan. The resulting multi-contrast images can be used to extract quantitative information on tissue microstructure. To make such…

Image and Video Processing · Electrical Eng. & Systems 2025-09-08 Natascha Niessen , Carolin M. Pirkl , Ana Beatriz Solana , Hannah Eichhorn , Veronika Spieker , Wenqi Huang , Tim Sprenger , Marion I. Menzel , Julia A. Schnabel

Purpose: Magnetization transfer (MT) and inhomogeneous MT (ihMT) contrasts are used in MRI to provide information about macromolecular tissue content. In particular, MT is sensitive to macromolecules and ihMT appears to be specific to…

Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image contrast, hindering data comparability and reproducibility…

Image and Video Processing · Electrical Eng. & Systems 2025-09-09 Daniel Scholz , Ayhan Can Erdur , Robbie Holland , Viktoria Ehm , Jan C. Peeken , Benedikt Wiestler , Daniel Rueckert

Missing data imputation (MDI) is a fundamental problem in many scientific disciplines. Popular methods for MDI use global statistics computed from the entire data set (e.g., the feature-wise medians), or build predictive models operating…

Machine Learning · Computer Science 2020-06-25 Indro Spinelli , Simone Scardapane , Aurelio Uncini

Magnetic resonance imaging (MRI) is a widely used neuroimaging technique that can provide images of different contrasts (i.e., modalities). Fusing this multi-modal data has proven particularly effective for boosting model performance in…

Computer Vision and Pattern Recognition · Computer Science 2020-02-13 Tao Zhou , Huazhu Fu , Geng Chen , Jianbing Shen , Ling Shao

In multi-contrast magnetic resonance imaging (MRI), compressed sensing theory can accelerate imaging by sampling fewer measurements within each contrast. The conventional optimization-based models suffer several limitations: strict…

Computer Vision and Pattern Recognition · Computer Science 2019-10-02 Liyan Sun , Zhiwen Fan , Yue Huang , Xinghao Ding , John Paisley

Multi-contrast MRI protocols increase the level of morphological information available for diagnosis. Yet, the number and quality of contrasts is limited in practice by various factors including scan time and patient motion. Synthesis of…

Image and Video Processing · Electrical Eng. & Systems 2019-09-26 Mahmut Yurt , Salman Ul Hassan Dar , Aykut Erdem , Erkut Erdem , Tolga Çukur

Magnetic resonance imaging (MRI) is essential for nasopharyngeal carcinoma (NPC) radiotherapy (RT), but practical constraints, such as patient discomfort, long scan times, and high costs often lead to incomplete modalities in clinical…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yao Pu , Yiming Shi , Zhenxi Zhang , Peixin Yu , Yitao Zhuang , Xiang Wang , Hongzhao Chen , Jing Cai , Ge Ren

Cross-modality magnetic resonance (MR) image synthesis can be used to generate missing modalities from given ones. Existing (supervised learning) methods often require a large number of paired multi-modal data to train an effective…

Image and Video Processing · Electrical Eng. & Systems 2023-06-21 Yonghao Li , Tao Zhou , Kelei He , Yi Zhou , Dinggang Shen
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