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Min Zhu

5 accepted papers

2026

GeoCoBox: Box-supervised 3D Tumor Segmentation via Geometric Co-embedding

AAAI 2026technical

Data economics drives AI by optimizing data usage, reducing costs, and enhancing efficiency. In 3D tumor segmentation, efficiency is crucial due to the high demand for labor-intensive manual annotations. Box-supervised segmentation offers a promising alternative but is constrained by tumor morpholog

Cited by 1SourcePDFScholar
2026

SegMoTE: Token-Level Mixture of Experts for Medical Image Segmentation

CVPR 2026

Medical image segmentation is vital for clinical diagnosis and quantitative analysis, yet remains challenging due to the heterogeneity of imaging modalities and the high cost of pixel-level annotations. Although general interactive segmentation models like SAM have achieved remarkable progress, thei

Cited by 0SourceScholar
2025

Interactive Medical Image Segmentation: A Benchmark Dataset and Baseline

CVPR 2025poster

Interactive Medical Image Segmentation (IMIS) has long been constrained by the limited availability of large-scale, diverse, and densely annotated datasets, which hinders model generalization and consistent evaluation across different models. In this paper, we introduce the IMed-361M benchmark datas…

2023

$\mathbf{\mathbb{E}^{FWI}}$: Multiparameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

NeurIPS 2023poster

Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO$_2$ sequestration and energy exploration (e.g., hydrogen and geothermal). Elastic full waveform inversion (FWI) is widely applied for characterizing reservoir properti…