Intracytoplasmic sperm injection (ICSI) operators frequently adjust the field-of-view (FOV) during procedures, which interrupts workflow and increases procedure time. Conventional microscopes require manual objective lens switching and illumination adjustments to achieve different FOV sizes.
arXiv:2609.07336v2 Announce Type: replace
Abstract: Morphology of the sub-basal nerve plexus (SNP) reflects peripheral nerve health, and corneal confocal microscopy (CCM) provides an important means...
By Qincheng Qiao, Puli Zhang, Jian Zhou, Xinguo Hou
Background: Laparoscopic camera navigation (LCN) is a critical skill, yet its current assessment typically relies on manual rating systems which are time-consuming and difficult to scale. Automated feedback could significantly enhance surgical training by providing immediate, standardized metrics.
arXiv:2609.28312v1 Announce Type: cross
Abstract: We present VGM-VS, a visual servoing method built on a pretrained feed-forward visual geometry model. Given the current view and a reference image ca...
By Yimin Pan, Sen Wang, You Zhou, Jianfeng Gao, Pengbo Sun, Ahmed M. Naguib, Zoltan-Csaba Marton
The paper introduces a semantic RGB–Depth framework for assessing microsurgical skill from microscopic stereo videos. It fuses sparse metric stereo depth with dense monocular depth to create a dense geometric scene representation, which is combined with semantically segmented RGB streams of instruments and anatomy. Using a hierarchical attention architecture, the model achieves an F1 score of 0.938 for skill-level classification, outperforming RGB-only and depth-only baselines.
By Jecia Z. Y. Mao, Sue M. Cho, Francis X. Creighton, Deepa Galaiya, Russell H. Taylor, Manish Sahu
We present VGM-VS, a visual servoing method built on a pretrained feed-forward visual geometry model. Given the current view and a reference image captured at the target configuration, we estimate the...