35 citations · 35 across the 4 of their papers we have counts for
4 papers
Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift
Joshua Talks, Kevin Marchesini, Luca Lumetti +2
Model reuse offers a solution to the challenges of segmentation in biomedical imaging, where high data annotation costs remain a major bottleneck for deep learning. However, althou…
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
Taming Mambas for Voxel Level 3D Medical Image Segmentation
Luca Lumetti, Vittorio Pipoli, Kevin Marchesini +3
Recently, the field of 3D medical segmentation has been dominated by deep learning models employing Convolutional Neural Networks (CNNs) and Transformer-based architectures, each w…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…