Difference between revisions of "News/2026"
Jump to navigation
Jump to search
(ACTRIMS 2026 news.) |
(Typo.) |
||
| Line 4: | Line 4: | ||
__NOTOC__ | __NOTOC__ | ||
{{h3|February}} | {{h3|February}} | ||
| − | [[File:2026-ACTRIMS-Hays-Poster-crop.png|thumb|250px|link=https://iacl.ece.jhu.edu/images/8/8c/2026-ACTRIMS-Hays-Poster-crop.png|Savannah Hays presents '''"The Impact of Site Variability on Volumetric Analysis in a Multi-Site MRI Dataset: A Case for Image Harmonization"''' at the {{iacl-pub actrims2026}}]] | + | [[File:2026-ACTRIMS-Hays-Poster-crop.png|thumb|250px|link=https://iacl.ece.jhu.edu/images/8/8c/2026-ACTRIMS-Hays-Poster-crop.png|Savannah P. Hays presents '''"The Impact of Site Variability on Volumetric Analysis in a Multi-Site MRI Dataset: A Case for Image Harmonization"''' at the {{iacl-pub actrims2026}}]] |
| − | * Savannah Hays presented '''"The Impact of Site Variability on Volumetric Analysis in a Multi-Site MRI Dataset: A Case for Image Harmonization"''' at the {{iacl-pub actrims2026}} | + | * Savannah P. Hays presented '''"The Impact of Site Variability on Volumetric Analysis in a Multi-Site MRI Dataset: A Case for Image Harmonization"''' at the {{iacl-pub actrims2026}} |
Revision as of 16:02, 9 February 2026
2026
February
- Savannah P. Hays presented "The Impact of Site Variability on Volumetric Analysis in a Multi-Site MRI Dataset: A Case for Image Harmonization" at the 11th annual Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS), San Diego, CA, February 5–7, 2026.
January
- Dr. Zhang's paper titled "UNISELF: A Unified Network with Instance Normalization and Self-Ensembled Lesion Fusion for Multiple Sclerosis Lesion Segmentation" appears in Medical Image Analysis.
- Our paper titled "Unsupervised learning of spatially varying regularization for diffeomorphic image registration" led by Dr. Junyu Chen is available from Medical Image Analysis.
- Savannah P. Hays has her first journal article published in SPIE Journal of Medical Imaging, titled "Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures".
