Cine cardiac magnetic resonance segmentation using temporal-spatial adaptation of prompt-enabled segment-anything-model: a feasibility study
ABSTRACT: Background: We propose an approach to adapt a segmentation foundation model, segment-anything-model (SAM), for cine cardiovascular magnetic resonance (CMR) segmentation and evaluate its generalization performance on unseen datasets. Methods: We present our model, cineCMR-SAM, which introd...
Saved in:
| Main Authors: | Zhennong Chen, Sekeun Kim, Hui Ren, Sunghwan Kim, Siyeop Yoon, Quanzheng Li, Xiang Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Journal of Cardiovascular Magnetic Resonance |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1097664725000717 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GDPGO-SAM: An Unsupervised Fine Segmentation of Desert Vegetation Driven by Grounding DINO Prompt Generation and Optimization Segment Anything Model
by: Shuzhen Hua, et al.
Published: (2025-02-01) -
MAET-SAM: Magneto-Acousto-Electrical Tomography segmentation network based on the segment anything model
by: Shuaiyu Bu, et al.
Published: (2025-02-01) -
Tooth segmentation on multimodal images using adapted segment anything model
by: Peijuan Wang, et al.
Published: (2025-04-01) -
Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis
by: Yan Liu, et al.
Published: (2025-03-01) -
A Coherent Approach-Based Fine-Tuning of Segment Anything Model Plus Watershed Algorithm for Instance Segmentation of Mitochondria in Electron Microscopy Images
by: Zahra Faska, et al.
Published: (2025-01-01)