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本公開「MRMS」2026年度

最終更新日: 2026年10月8日New

2026Volume 25Issue 4

＜MAJOR PAPER＞

Deep Learning–driven Segmentation of Breast Cancer MR Imaging Using a Hybrid ResNet–Transformer Architecture and Cross-dataset Validation

Yongjian Sui, et al.

Effects of Artificial Intelligence–based Reconstruction on Image Quality and Voxel-based Morphometry Analysis of Atrophy in Accelerated MPRAGE

Tatsunori Horie, et al.

Multi-pool Model–based Amide Proton Transfer Imaging for Tumor Characterization and Risk Stratification in Endometrial Carcinoma

Yasukage Takami, et al.

Atrial Function and the Pressure–Strain Relationship in Patients with Fontan Circulation

Hideharu Oka, et al.

Associating a Polygenic Risk Score for Multiple Sclerosis with Brain MRI Metrics and Cognitive Performance in Healthy UK Biobank Participants

Chenyu Feng, et al.

Hyperintense Signals in Cerebral Blood Flow Maps of Mice Acquired with Pseudo-continuous Arterial Spin Labeling MR Imaging

Xiuli Yang, et al.

Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning

Shohei Fujita, et al.

Parameter Estimation for the Intravoxel Incoherent Motion-diffusional Kurtosis Imaging Model Using Synthetic Q-space Learning Toward Breast Tumor Diagnosis

Kousei Konya, et al.

Structure-preserving Image-quality Enhancement for 3D Synthetic FLAIR Using a 3D U-Net with Content and Style Losses

Satoru Kamio, et al.

Multimodal Quantitative Parameter Mapping Characterizes Low-dimensional Feature Organization and Tract-specific Signatures in White Matter

Emi Sato, et al.

Usefulness of Adaptive Complex Signal Average Diffusion-weighted MR Imaging of the Abdomen

Miwa Matsukuma, et al.

WCCAN: Windowed Cross-contrast Attention Network for Multi-contrast Brain MR Image Super-resolution

Rania Saoudi, et al.

Relationship between Vascular Tortuosity Rate and Atherosclerotic Risk Factors in Patients with Carotid Artery Stenosis

Masanori Tsuji, et al.

＜TECHNICAL NOTE＞

Development of a Dedicated Prostate Phantom for Technical Evaluation of Diffusion-weighted MR Imaging Sequences

Kazunori Ohashi, et al.

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