Cross-view discrepancy-dependency network for volumetric medical image segmentation
S Zhong, W Wang, Q Feng, Y Zhang, Z Ning - Medical Image Analysis, 2025 - Elsevier
The limited data poses a crucial challenge for deep learning-based volumetric medical
image segmentation, and many methods have tried to represent the volume by its …
image segmentation, and many methods have tried to represent the volume by its …
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training
C Li, H Zhu, RI Sultan, HB Ebadian, P Khanduri… - arXiv preprint arXiv …, 2024 - arxiv.org
In the diverse field of medical imaging, automatic segmentation has numerous applications
and must handle a wide variety of input domains, such as different types of Computed …
and must handle a wide variety of input domains, such as different types of Computed …
Novel Transformer Architectures for 3D Multi-Modal and Multi-Organ Medical Image Segmentation
C Li - 2024 - search.proquest.com
Medical image segmentation is a crucial process in medical imaging analysis, enabling
precise delineation of anatomical structures and pathological regions. This dissertation …
precise delineation of anatomical structures and pathological regions. This dissertation …
Swin UNet: a memory-efficient and accurate deep learning model for medical image segmentation
J Pan - Third International Conference on Machine Vision …, 2024 - spiedigitallibrary.org
Medical image segmentation is a challenging and important task that aims to identify and
separate different anatomical structures or pathological regions from complex and noisy …
separate different anatomical structures or pathological regions from complex and noisy …