Segment Anything Model (SAM) for Medical Image Segmentation: A Preliminary Review

L Zhang, X Deng, Y Lu - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
Medical image segmentation is a critical component in a variety of clinical applications,
facilitating accurate diagnosis and treatment planning. The Segment Anything Model (SAM) …

Visual–tactile learning of robotic cable-in-duct installation skills

B Duan, K Qian, A Liu, S Luo - Automation in Construction, 2025 - Elsevier
Cable-in-duct installation is one of the most challenging contact-rich interior finishing tasks
for construction robots. Such precise robotic cable manipulation skills are expected to be …

Segment any medical model extended

Y Liu, J Zhang, A Diaz-Pinto, H Li… - Medical Imaging …, 2024 - spiedigitallibrary.org
The Segment Anything Model (SAM) has drawn significant attention from researchers who
work on medical image segmentation because of its generalizability. However, researchers …

Real Time Multi Organ Classification on Computed Tomography Images

HZ Yerebakan, Y Shinagawa, GH Valadez - MICCAI Workshop on Data …, 2024 - Springer
Organ segmentation is a fundamental task in medical imaging since it is useful for many
clinical automation pipelines. However, some tasks do not require full segmentation …